# NLP Text Processing methods

### NLTK

We can use some available data sets for educational purpose. One of such source are NLTK book corporas. To download it we need to do the following:

```python
import nltk
nltk.download('book')
```

    [nltk_data] Downloading collection 'book'
    [nltk_data]    |
    [nltk_data]    | Downloading package abc to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/abc.zip.
    [nltk_data]    | Downloading package brown to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/brown.zip.
    [nltk_data]    | Downloading package chat80 to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/chat80.zip.
    [nltk_data]    | Downloading package cmudict to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/cmudict.zip.
    [nltk_data]    | Downloading package conll2000 to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/conll2000.zip.
    [nltk_data]    | Downloading package conll2002 to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/conll2002.zip.
    [nltk_data]    | Downloading package dependency_treebank to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/dependency_treebank.zip.
    [nltk_data]    | Downloading package genesis to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/genesis.zip.
    [nltk_data]    | Downloading package gutenberg to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/gutenberg.zip.
    [nltk_data]    | Downloading package ieer to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/ieer.zip.
    [nltk_data]    | Downloading package inaugural to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/inaugural.zip.
    [nltk_data]    | Downloading package movie_reviews to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/movie_reviews.zip.
    [nltk_data]    | Downloading package nps_chat to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/nps_chat.zip.
    [nltk_data]    | Downloading package names to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/names.zip.
    [nltk_data]    | Downloading package ppattach to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/ppattach.zip.
    [nltk_data]    | Downloading package reuters to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    | Downloading package senseval to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/senseval.zip.
    [nltk_data]    | Downloading package state_union to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/state_union.zip.
    [nltk_data]    | Downloading package stopwords to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/stopwords.zip.
    [nltk_data]    | Downloading package swadesh to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/swadesh.zip.
    [nltk_data]    | Downloading package timit to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/timit.zip.
    [nltk_data]    | Downloading package treebank to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/treebank.zip.
    [nltk_data]    | Downloading package toolbox to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/toolbox.zip.
    [nltk_data]    | Downloading package udhr to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/udhr.zip.
    [nltk_data]    | Downloading package udhr2 to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/udhr2.zip.
    [nltk_data]    | Downloading package unicode_samples to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/unicode_samples.zip.
    [nltk_data]    | Downloading package webtext to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/webtext.zip.
    [nltk_data]    | Downloading package wordnet to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/wordnet.zip.
    [nltk_data]    | Downloading package wordnet_ic to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/wordnet_ic.zip.
    [nltk_data]    | Downloading package words to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/words.zip.
    [nltk_data]    | Downloading package maxent_treebank_pos_tagger to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping taggers/maxent_treebank_pos_tagger.zip.
    [nltk_data]    | Downloading package maxent_ne_chunker to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping chunkers/maxent_ne_chunker.zip.
    [nltk_data]    | Downloading package universal_tagset to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping taggers/universal_tagset.zip.
    [nltk_data]    | Downloading package punkt to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping tokenizers/punkt.zip.
    [nltk_data]    | Downloading package book_grammars to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping grammars/book_grammars.zip.
    [nltk_data]    | Downloading package city_database to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping corpora/city_database.zip.
    [nltk_data]    | Downloading package tagsets to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping help/tagsets.zip.
    [nltk_data]    | Downloading package panlex_swadesh to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    | Downloading package averaged_perceptron_tagger to
    [nltk_data]    |     /home/kprzystalski/nltk_data...
    [nltk_data]    |   Unzipping taggers/averaged_perceptron_tagger.zip.
    [nltk_data]    |
    [nltk_data]  Done downloading collection book

    True

To check what kind of books are available we need to import these and print the list as following:

```python
from nltk.book import *
texts()
```

    *** Introductory Examples for the NLTK Book ***
    Loading text1, ..., text9 and sent1, ..., sent9
    Type the name of the text or sentence to view it.
    Type: 'texts()' or 'sents()' to list the materials.
    text1: Moby Dick by Herman Melville 1851
    text2: Sense and Sensibility by Jane Austen 1811
    text3: The Book of Genesis
    text4: Inaugural Address Corpus
    text5: Chat Corpus
    text6: Monty Python and the Holy Grail
    text7: Wall Street Journal
    text8: Personals Corpus
    text9: The Man Who Was Thursday by G . K . Chesterton 1908
    text1: Moby Dick by Herman Melville 1851
    text2: Sense and Sensibility by Jane Austen 1811
    text3: The Book of Genesis
    text4: Inaugural Address Corpus
    text5: Chat Corpus
    text6: Monty Python and the Holy Grail
    text7: Wall Street Journal
    text8: Personals Corpus
    text9: The Man Who Was Thursday by G . K . Chesterton 1908

NLTK Text object does have some useful methods that you can find here: [NLTK Text Docs](http://www.nltk.org/api/nltk.html#nltk.text.Text). Some are used below.

#### Word and sentences similarity

Word does have different meanings. This makes the comparison and analysis a bit more complex.

```python
text6.concordance("King")

text6.count("King")
```

    Displaying 25 of 38 matches:
    CENE 1 : [ wind ] [ clop clop clop ] KING ARTHUR : Whoa there ! [ clop clop cl
    ragon , from the castle of Camelot . King of the Britons , defeator of the Sax
     CART - MASTER : I dunno . Must be a king . CUSTOMER : Why ? CART - MASTER : H
     all over him . SCENE 3 : [ thud ] [ King Arthur music ] [ thud thud thud ] [
     Arthur music ] [ thud thud thud ] [ King Arthur music stops ] ARTHUR : Old wo
    e an inferior ! ARTHUR : Well , I am king ! DENNIS : Oh king , eh , very nice
    HUR : Well , I am king ! DENNIS : Oh king , eh , very nice . And how d ' you g
    o you do , good lady . I am Arthur , King of the Britons . Who ' s castle is t
    s . Who ' s castle is that ? WOMAN : King of the who ? ARTHUR : The Britons .
    . We are all Britons , and I am your king . WOMAN : I didn ' t know we had a k
    g . WOMAN : I didn ' t know we had a king . I thought we were an autonomous co
    ink he is ? Heh . ARTHUR : I am your king ! WOMAN : Well , I didn ' t vote for
     . WOMAN : Well , how did you become king then ? ARTHUR : The Lady of the Lake
    inging stops ] That is why I am your king ! DENNIS : Listen , strange women ly
    ou saw it , didn ' t you SCENE 4 : [ King Arthur music ] [ music stops ] BLACK
    sic stops ] BLACK KNIGHT : Aaagh ! [ King Arthur music ] [ music stops ] BLACK
    GHT : Aaagh ! GREEN KNIGHT : Ooh ! [ King Arthur music ] [ music stops ] [ sta
    NIGHT : Aagh ! GREEN KNIGHT : Oh ! [ King Arthur music ] Ooh ! [ music stops ]
    Sir Knight . [ pause ] I am Arthur , King of the Britons . [ pause ] I seek th
    ll die . ARTHUR : I command you , as King of the Britons , to stand aside ! BL
     of science ? ARTHUR : I am Arthur , King of the Britons . BEDEVERE : My liege
    e Sir Bedevere was the first to join King Arthur ' s knights , but other illus
    ngels sing ] GOD : Arthur ! Arthur , King of the Britons ! Oh , don ' t grovel
     Yes , Lord . GOD : Right ! Arthur , King of the Britons , your Knights of the
    GALAHAD : God be praised SCENE 8 : [ King Arthur music ] [ clop clop clop ] AR

    27

We can also build a Corpus from a plain text. See the example below.

```python
from nltk.corpus import PlaintextCorpusReader
from nltk.tokenize.regexp import WordPunctTokenizer
from nltk.data import LazyLoader

trump = PlaintextCorpusReader('../datasets/','trump.txt',word_tokenizer=WordPunctTokenizer(),
             sent_tokenizer=LazyLoader(
                 'tokenizers/punkt/english.pickle'),
             encoding='utf8')
print(trump)
trump.words()
```

    <PlaintextCorpusReader in '/home/kprzystalski/workshop/datasets'>

    ['Thank', 'you', 'very', 'much', '.', 'Mr', '.', ...]

Corpuses contain large amount of texts, say multiple books, couple hundreds of articles from various magazines etc. NLTK has chosen a few books from over 25,000 pieces available in the whole dataset. We are going to pick Bible and Shakespeare's Macbeth in order to compare a few statistics between them. Let's take a look at other corporas and check the gutenberg and check the word distribution:

```python
import matplotlib.pyplot as plt
import seaborn as sns

sns.set_style('whitegrid') # general display style of seaborn
# how to display plot in notebook, jupyter's magic command
%matplotlib inline

# Download necessary texts
nltk.download('gutenberg')
nltk.download('stopwords')

print("Books available in gutenberg dataset:")
nltk.corpus.gutenberg.fileids()
```

    Books available in gutenberg dataset:

    [nltk_data] Downloading package gutenberg to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package gutenberg is already up-to-date!
    [nltk_data] Downloading package stopwords to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package stopwords is already up-to-date!

    ['austen-emma.txt',
     'austen-persuasion.txt',
     'austen-sense.txt',
     'bible-kjv.txt',
     'blake-poems.txt',
     'bryant-stories.txt',
     'burgess-busterbrown.txt',
     'carroll-alice.txt',
     'chesterton-ball.txt',
     'chesterton-brown.txt',
     'chesterton-thursday.txt',
     'edgeworth-parents.txt',
     'melville-moby_dick.txt',
     'milton-paradise.txt',
     'shakespeare-caesar.txt',
     'shakespeare-hamlet.txt',
     'shakespeare-macbeth.txt',
     'whitman-leaves.txt']

```python
nltk.corpus.stopwords.words("english")
```

    ['i',
     'me',
     'my',
     'myself',
     'we',
     'our',
     'ours',
     'ourselves',
     'you',
     "you're",
     "you've",
     "you'll",
     "you'd",
     'your',
     'yours',
     'yourself',
     'yourselves',
     'he',
     'him',
     'his',
     'himself',
     'she',
     "she's",
     'her',
     'hers',
     'herself',
     'it',
     "it's",
     'its',
     'itself',
     'they',
     'them',
     'their',
     'theirs',
     'themselves',
     'what',
     'which',
     'who',
     'whom',
     'this',
     'that',
     "that'll",
     'these',
     'those',
     'am',
     'is',
     'are',
     'was',
     'were',
     'be',
     'been',
     'being',
     'have',
     'has',
     'had',
     'having',
     'do',
     'does',
     'did',
     'doing',
     'a',
     'an',
     'the',
     'and',
     'but',
     'if',
     'or',
     'because',
     'as',
     'until',
     'while',
     'of',
     'at',
     'by',
     'for',
     'with',
     'about',
     'against',
     'between',
     'into',
     'through',
     'during',
     'before',
     'after',
     'above',
     'below',
     'to',
     'from',
     'up',
     'down',
     'in',
     'out',
     'on',
     'off',
     'over',
     'under',
     'again',
     'further',
     'then',
     'once',
     'here',
     'there',
     'when',
     'where',
     'why',
     'how',
     'all',
     'any',
     'both',
     'each',
     'few',
     'more',
     'most',
     'other',
     'some',
     'such',
     'no',
     'nor',
     'not',
     'only',
     'own',
     'same',
     'so',
     'than',
     'too',
     'very',
     's',
     't',
     'can',
     'will',
     'just',
     'don',
     "don't",
     'should',
     "should've",
     'now',
     'd',
     'll',
     'm',
     'o',
     're',
     've',
     'y',
     'ain',
     'aren',
     "aren't",
     'couldn',
     "couldn't",
     'didn',
     "didn't",
     'doesn',
     "doesn't",
     'hadn',
     "hadn't",
     'hasn',
     "hasn't",
     'haven',
     "haven't",
     'isn',
     "isn't",
     'ma',
     'mightn',
     "mightn't",
     'mustn',
     "mustn't",
     'needn',
     "needn't",
     'shan',
     "shan't",
     'shouldn',
     "shouldn't",
     'wasn',
     "wasn't",
     'weren',
     "weren't",
     'won',
     "won't",
     'wouldn',
     "wouldn't"]

```python
%matplotlib inline

def lexical_richness(text: str) -> float:
  # Unique words in text divided by the total amount of words
  words = nltk.Text(nltk.corpus.gutenberg.words(text))
  return len(set(words))/len(words)

macbeth = "shakespeare-macbeth.txt"
bible = "bible-kjv.txt"

print("Macbeth richness: {}".format(lexical_richness(macbeth)))
print("Bible richness: {}".format(lexical_richness(bible)))

# Removing stopwords like: , . and or
bible_words = [
    word
    for word in nltk.corpus.gutenberg.words(bible)
    if word not in nltk.corpus.stopwords.words("english") and word.isalpha()
]

words_distribution = nltk.probability.FreqDist(bible_words)
print("Words occuring most often in Bible:")
display(words_distribution.plot(15))
```

### Regular expression

The first solution that comes to our mind when it comes to text processing are regular expression. It is usually the best solution in software development. It is also used in many tools that we have mentioned before. Let's take an example to do a short recap how to use regular expressions in Python.

```python
example = "JU is a great company with many great developers."

import re

pattern = "\\s+"
words = re.split(pattern, example)
print(words)
```

    ['JU', 'is', 'a', 'great', 'company', 'with', 'many', 'great', 'developers.']

Python does have some methods for Strings that can do the same as above, but with less code.

```python
words = example.split(' ')
print(words)

text = "Well, what can I say about regexes? \
They are quite annoying to be honest, but once you get a grasp you're gonna be fine. \
Yeah, I could use some basic boring text, here you go if that's what you miss: \
Ala ma kota, kot ma Alę. m?ke a m1sta.e and see what happens... \
This sentence: 'Mr. & Mrs. Smith, been looking for easter egg here, failed."
text.split(' ')
```

    ['JU', 'is', 'a', 'great', 'company', 'with', 'many', 'great', 'developers.']

    ['Well,',
     'what',
     'can',
     'I',
     'say',
     'about',
     'regexes?',
     'They',
     'are',
     'quite',
     'annoying',
     'to',
     'be',
     'honest,',
     'but',
     'once',
     'you',
     'get',
     'a',
     'grasp',
     "you're",
     'gonna',
     'be',
     'fine.',
     'Yeah,',
     'I',
     'could',
     'use',
     'some',
     'basic',
     'boring',
     'text,',
     'here',
     'you',
     'go',
     'if',
     "that's",
     'what',
     'you',
     'miss:',
     'Ala',
     'ma',
     'kota,',
     'kot',
     'ma',
     'Alę.',
     'm?ke',
     'a',
     'm1sta.e',
     'and',
     'see',
     'what',
     'happens...',
     'This',
     'sentence:',
     "'Mr.",
     '&',
     'Mrs.',
     'Smith,',
     'been',
     'looking',
     'for',
     'easter',
     'egg',
     'here,',
     'failed.']

That was too naive, let's make something more intelligent:

```python
print("Using regex:")
display(re.split('(?<=[.!?]) +',text))
```

    Using regex:

    ['Well, what can I say about regexes?',
     "They are quite annoying to be honest, but once you get a grasp you're gonna be fine.",
     "Yeah, I could use some basic boring text, here you go if that's what you miss: Ala ma kota, kot ma Alę.",
     'm?ke a m1sta.e and see what happens...',
     "This sentence: 'Mr.",
     '& Mrs.',
     'Smith, been looking for easter egg here, failed.']

Our regex only splits the text if either of . ! ? is followed by one or more whitespace signs. This approach is quite powerful, yet limited (as could be seen), keep in mind it has it's uses but is far from perfect (later we will see more sophisticated approaches).

All in all, when faced with a choice: do something using traditional methods or using machine learning, ALWAYS pick the first one.

```python
# Examples of some other regex functions

text = re.sub(r"Mr. & Mrs. Smith", "Now works like a charm", text) #substitute string
found_text = re.findall(", been .*,", text) # find all occurences of string
display(found_text)

# findall returns list, we need to access it's element
re.sub(found_text[0], " but life", text)
```

    [', been looking for easter egg here,']

    "Well, what can I say about regexes? They are quite annoying to be honest, but once you get a grasp you're gonna be fine. Yeah, I could use some basic boring text, here you go if that's what you miss: Ala ma kota, kot ma Alę. m?ke a m1sta.e and see what happens... This sentence: 'Now works like a charm but life failed."

### Tokenization

NLTK is a more advanced tool than just regular expressions. We can easily tokenize sentences. Tokenization is a process of getting words from sentences. **Tokenizers** are used to divide a string into it's logical subsets. Above, we have used the sentence tokenizer. Tokenization on the other hand is a common name for dividing a text into separate words and can be done in NLTK using word_tokenizer:

```python
tokens = nltk.word_tokenize(example)
print("Tokens: " + str(tokens))
```

    Tokens: ['JU', 'is', 'a', 'great', 'company', 'with', 'many', 'great', 'developers', '.']

After a little fun we can use nltk to separate text into sentences in 'smarter' fashion:

```python
from nltk.tokenize import sent_tokenize

nltk.download('punkt')

sent_tokenize(text)
```

    [nltk_data] Downloading package punkt to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package punkt is already up-to-date!

    ['Well, what can I say about regexes?',
     "They are quite annoying to be honest, but once you get a grasp you're gonna be fine.",
     "Yeah, I could use some basic boring text, here you go if that's what you miss: Ala ma kota, kot ma Alę.",
     'm?ke a m1sta.e and see what happens...',
     "This sentence: 'Now works like a charm, been looking for easter egg here, failed."]

__Tokenizers__ are used to divide a string into it's logical subsets. Above, we
have used
the sentence tokenizer. __Tokenization__ on the other hand is a common
name for dividing
a text into separate words and can be done in NLTK using
__word_tokenizer__:

```python
from nltk.tokenize import word_tokenize, TweetTokenizer
from nltk.tokenize import TweetTokenizer # Yes, this tokenizer was based on Tweets

text = "This is a cooool #dummysmiley: :-) :-P <3 and some arrows < > -> <--"
print("Normal tokenizer:")
print(word_tokenize(text))

print("This tokenizer is better suited for emoji handling")
twitter_tokenizer = TweetTokenizer()
twitter_tokenizer.tokenize(text)
```

    Normal tokenizer:
    ['This', 'is', 'a', 'cooool', '#', 'dummysmiley', ':', ':', '-', ')', ':', '-P', '<', '3', 'and', 'some', 'arrows', '<', '>', '-', '>', '<', '--']
    This tokenizer is better suited for emoji handling

    ['This',
     'is',
     'a',
     'cooool',
     '#dummysmiley',
     ':',
     ':-)',
     ':-P',
     '<3',
     'and',
     'some',
     'arrows',
     '<',
     '>',
     '->',
     '<--']

As you can see there are other tokenizers available and each is focused on
different
'kind' of tokenization.

They are usually implemented as a set of
complicated rules trailed down to certain language
(e.g. will be different for
polish and english) and __ARE NOT__ a subset of machine
learning (in
this part of course at least).

Here are some other NLTK's tokenizers you could
use:

- __PunktTokenizer__: been used above for sentence tokenization. This one
actually uses unsupervised algorithm to infer sentence boundaries.
- __NISTTokenizer__: tokenizer for non-european text (say in Chinese).
- __SExprTokenizer__: find parenthesized expressions in strings, see below:

```python
from nltk.tokenize import SExprTokenizer

SExprTokenizer().tokenize('(a b (c d)) e f (g)')
```

    ['(a b (c d))', 'e', 'f', '(g)']

### Tagging

What is great with NLTK is that we can tag each word. A tag give us a meaning of a word. We can think about it as a type of word.

```python
tags = nltk.pos_tag(tokens)
print("Tagged: " + str(tags))
```

    Tagged: [('JU', 'NNP'), ('is', 'VBZ'), ('a', 'DT'), ('great', 'JJ'), ('company', 'NN'), ('with', 'IN'), ('many', 'JJ'), ('great', 'JJ'), ('developers', 'NNS'), ('.', '.')]

Some tags are shown in the table below.

| tag  | short | description   |
|------|-------|---------------|
| DT   | determiner | all an another any both del each either every half la many much nary neither no some such that the them these this those |
| IN   | preposition or conjunction, subordinating | astride among uppon whether out inside pro despite on by throughout below within for towards near behind atop around if like until below next into if beside ... |
| JJ   | adjective or numeral, ordinal | third ill-mannered pre-war regrettable oiled calamitous first separable ectoplasmic battery-powered participatory fourth still-to-be-named multilingual multi-disciplinary ... |
| NN   | noun, common, singular or mass | common-carrier cabbage knuckle-duster Casino afghan shed thermostat investment slide humour falloff slick wind hyena override subhumanity machinist ... |
| NNP  | noun, proper, singular | Motown Venneboerger Czestochowa Ranzer Conchita Trumplane Christos Oceanside Escobar Kreisler Sawyer Cougar Yvette Ervin ODI Darryl CTCA Shannon A.K.C. Meltex Liverpool ... |
| NNS  | noun, common, plural | undergraduates scotches bric-a-brac products bodyguards facets coasts divestitures storehouses designs clubs fragrances averages subjectivists apprehensions muses factory-jobs ... |
| VBZ  | verb, present tense, 3rd person singular | bases reconstructs marks mixes displeases seals carps weaves snatches slumps stretches authorizes smolders pictures emerges stockpiles seduces fizzes uses bolsters slaps speaks pleads ... |

To get the full list of tags, use the following code:

```python
nltk.download('tagsets')
nltk.help.upenn_tagset()
```

    $: dollar
        $ -$ --$ A$ C$ HK$ M$ NZ$ S$ U.S.$ US$
    '': closing quotation mark
        ' ''
    (: opening parenthesis
        ( [ {
    ): closing parenthesis
        ) ] }
    ,: comma
        ,
    --: dash
        --
    .: sentence terminator
        . ! ?
    :: colon or ellipsis
        : ; ...
    CC: conjunction, coordinating
        & 'n and both but either et for less minus neither nor or plus so
        therefore times v. versus vs. whether yet
    CD: numeral, cardinal
        mid-1890 nine-thirty forty-two one-tenth ten million 0.5 one forty-
        seven 1987 twenty '79 zero two 78-degrees eighty-four IX '60s .025
        fifteen 271,124 dozen quintillion DM2,000 ...
    DT: determiner
        all an another any both del each either every half la many much nary
        neither no some such that the them these this those
    EX: existential there
        there
    FW: foreign word
        gemeinschaft hund ich jeux habeas Haementeria Herr K'ang-si vous
        lutihaw alai je jour objets salutaris fille quibusdam pas trop Monte
        terram fiche oui corporis ...
    IN: preposition or conjunction, subordinating
        astride among uppon whether out inside pro despite on by throughout
        below within for towards near behind atop around if like until below
        next into if beside ...
    JJ: adjective or numeral, ordinal
        third ill-mannered pre-war regrettable oiled calamitous first separable
        ectoplasmic battery-powered participatory fourth still-to-be-named
        multilingual multi-disciplinary ...
    JJR: adjective, comparative
        bleaker braver breezier briefer brighter brisker broader bumper busier
        calmer cheaper choosier cleaner clearer closer colder commoner costlier
        cozier creamier crunchier cuter ...
    JJS: adjective, superlative
        calmest cheapest choicest classiest cleanest clearest closest commonest
        corniest costliest crassest creepiest crudest cutest darkest deadliest
        dearest deepest densest dinkiest ...
    LS: list item marker
        A A. B B. C C. D E F First G H I J K One SP-44001 SP-44002 SP-44005
        SP-44007 Second Third Three Two * a b c d first five four one six three
        two
    MD: modal auxiliary
        can cannot could couldn't dare may might must need ought shall should
        shouldn't will would
    NN: noun, common, singular or mass
        common-carrier cabbage knuckle-duster Casino afghan shed thermostat
        investment slide humour falloff slick wind hyena override subhumanity
        machinist ...
    NNP: noun, proper, singular
        Motown Venneboerger Czestochwa Ranzer Conchita Trumplane Christos
        Oceanside Escobar Kreisler Sawyer Cougar Yvette Ervin ODI Darryl CTCA
        Shannon A.K.C. Meltex Liverpool ...
    NNPS: noun, proper, plural
        Americans Americas Amharas Amityvilles Amusements Anarcho-Syndicalists
        Andalusians Andes Andruses Angels Animals Anthony Antilles Antiques
        Apache Apaches Apocrypha ...
    NNS: noun, common, plural
        undergraduates scotches bric-a-brac products bodyguards facets coasts
        divestitures storehouses designs clubs fragrances averages
        subjectivists apprehensions muses factory-jobs ...
    PDT: pre-determiner
        all both half many quite such sure this
    POS: genitive marker
        ' 's
    PRP: pronoun, personal
        hers herself him himself hisself it itself me myself one oneself ours
        ourselves ownself self she thee theirs them themselves they thou thy us
    PRP$: pronoun, possessive
        her his mine my our ours their thy your
    RB: adverb
        occasionally unabatingly maddeningly adventurously professedly
        stirringly prominently technologically magisterially predominately
        swiftly fiscally pitilessly ...
    RBR: adverb, comparative
        further gloomier grander graver greater grimmer harder harsher
        healthier heavier higher however larger later leaner lengthier less-
        perfectly lesser lonelier longer louder lower more ...
    RBS: adverb, superlative
        best biggest bluntest earliest farthest first furthest hardest
        heartiest highest largest least less most nearest second tightest worst
    RP: particle
        aboard about across along apart around aside at away back before behind
        by crop down ever fast for forth from go high i.e. in into just later
        low more off on open out over per pie raising start teeth that through
        under unto up up-pp upon whole with you
    SYM: symbol
        % & ' '' ''. ) ). * + ,. < = > @ A[fj] U.S U.S.S.R * ** ***
    TO: "to" as preposition or infinitive marker
        to
    UH: interjection
        Goodbye Goody Gosh Wow Jeepers Jee-sus Hubba Hey Kee-reist Oops amen
        huh howdy uh dammit whammo shucks heck anyways whodunnit honey golly
        man baby diddle hush sonuvabitch ...
    VB: verb, base form
        ask assemble assess assign assume atone attention avoid bake balkanize
        bank begin behold believe bend benefit bevel beware bless boil bomb
        boost brace break bring broil brush build ...
    VBD: verb, past tense
        dipped pleaded swiped regummed soaked tidied convened halted registered
        cushioned exacted snubbed strode aimed adopted belied figgered
        speculated wore appreciated contemplated ...
    VBG: verb, present participle or gerund
        telegraphing stirring focusing angering judging stalling lactating
        hankerin' alleging veering capping approaching traveling besieging
        encrypting interrupting erasing wincing ...
    VBN: verb, past participle
        multihulled dilapidated aerosolized chaired languished panelized used
        experimented flourished imitated reunifed factored condensed sheared
        unsettled primed dubbed desired ...
    VBP: verb, present tense, not 3rd person singular
        predominate wrap resort sue twist spill cure lengthen brush terminate
        appear tend stray glisten obtain comprise detest tease attract
        emphasize mold postpone sever return wag ...
    VBZ: verb, present tense, 3rd person singular
        bases reconstructs marks mixes displeases seals carps weaves snatches
        slumps stretches authorizes smolders pictures emerges stockpiles
        seduces fizzes uses bolsters slaps speaks pleads ...
    WDT: WH-determiner
        that what whatever which whichever
    WP: WH-pronoun
        that what whatever whatsoever which who whom whosoever
    WP$: WH-pronoun, possessive
        whose
    WRB: Wh-adverb
        how however whence whenever where whereby whereever wherein whereof why
    ``: opening quotation mark
        ` ``

    [nltk_data] Downloading package tagsets to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package tagsets is already up-to-date!

We can find the token in NLTK's corporas too:

```python
text6.tokens
```

    ['SCENE',
     '1',
     ':',
     '[',
     'wind',
     ']',
     '[',
     'clop',
     'clop',
     'clop',
     ']',
     'KING',
     'ARTHUR',
     ':',
     'Whoa',
     'there',
     '!',
     '[',
     'clop',
     'clop',
     'clop',
     ']',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Halt',
     '!',
     'Who',
     'goes',
     'there',
     '?',
     'ARTHUR',
     ':',
     'It',
     'is',
     'I',
     ',',
     'Arthur',
     ',',
     'son',
     'of',
     'Uther',
     'Pendragon',
     ',',
     'from',
     'the',
     'castle',
     'of',
     'Camelot',
     '.',
     'King',
     'of',
     'the',
     'Britons',
     ',',
     'defeator',
     'of',
     'the',
     'Saxons',
     ',',
     'sovereign',
     'of',
     'all',
     'England',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Pull',
     'the',
     'other',
     'one',
     '!',
     'ARTHUR',
     ':',
     'I',
     'am',
     ',',
     '...',
     'and',
     'this',
     'is',
     'my',
     'trusty',
     'servant',
     'Patsy',
     '.',
     'We',
     'have',
     'ridden',
     'the',
     'length',
     'and',
     'breadth',
     'of',
     'the',
     'land',
     'in',
     'search',
     'of',
     'knights',
     'who',
     'will',
     'join',
     'me',
     'in',
     'my',
     'court',
     'at',
     'Camelot',
     '.',
     'I',
     'must',
     'speak',
     'with',
     'your',
     'lord',
     'and',
     'master',
     '.',
     'SOLDIER',
     '#',
     '1',
     ':',
     'What',
     '?',
     'Ridden',
     'on',
     'a',
     'horse',
     '?',
     'ARTHUR',
     ':',
     'Yes',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'You',
     "'",
     're',
     'using',
     'coconuts',
     '!',
     'ARTHUR',
     ':',
     'What',
     '?',
     'SOLDIER',
     '#',
     '1',
     ':',
     'You',
     "'",
     've',
     'got',
     'two',
     'empty',
     'halves',
     'of',
     'coconut',
     'and',
     'you',
     "'",
     're',
     'bangin',
     "'",
     "'",
     'em',
     'together',
     '.',
     'ARTHUR',
     ':',
     'So',
     '?',
     'We',
     'have',
     'ridden',
     'since',
     'the',
     'snows',
     'of',
     'winter',
     'covered',
     'this',
     'land',
     ',',
     'through',
     'the',
     'kingdom',
     'of',
     'Mercea',
     ',',
     'through',
     '--',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Where',
     "'",
     'd',
     'you',
     'get',
     'the',
     'coconuts',
     '?',
     'ARTHUR',
     ':',
     'We',
     'found',
     'them',
     '.',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Found',
     'them',
     '?',
     'In',
     'Mercea',
     '?',
     'The',
     'coconut',
     "'",
     's',
     'tropical',
     '!',
     'ARTHUR',
     ':',
     'What',
     'do',
     'you',
     'mean',
     '?',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Well',
     ',',
     'this',
     'is',
     'a',
     'temperate',
     'zone',
     '.',
     'ARTHUR',
     ':',
     'The',
     'swallow',
     'may',
     'fly',
     'south',
     'with',
     'the',
     'sun',
     'or',
     'the',
     'house',
     'martin',
     'or',
     'the',
     'plover',
     'may',
     'seek',
     'warmer',
     'climes',
     'in',
     'winter',
     ',',
     'yet',
     'these',
     'are',
     'not',
     'strangers',
     'to',
     'our',
     'land',
     '?',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Are',
     'you',
     'suggesting',
     'coconuts',
     'migrate',
     '?',
     'ARTHUR',
     ':',
     'Not',
     'at',
     'all',
     '.',
     'They',
     'could',
     'be',
     'carried',
     '.',
     'SOLDIER',
     '#',
     '1',
     ':',
     'What',
     '?',
     'A',
     'swallow',
     'carrying',
     'a',
     'coconut',
     '?',
     'ARTHUR',
     ':',
     'It',
     'could',
     'grip',
     'it',
     'by',
     'the',
     'husk',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'It',
     "'",
     's',
     'not',
     'a',
     'question',
     'of',
     'where',
     'he',
     'grips',
     'it',
     '!',
     'It',
     "'",
     's',
     'a',
     'simple',
     'question',
     'of',
     'weight',
     'ratios',
     '!',
     'A',
     'five',
     'ounce',
     'bird',
     'could',
     'not',
     'carry',
     'a',
     'one',
     'pound',
     'coconut',
     '.',
     'ARTHUR',
     ':',
     'Well',
     ',',
     'it',
     'doesn',
     "'",
     't',
     'matter',
     '.',
     'Will',
     'you',
     'go',
     'and',
     'tell',
     'your',
     'master',
     'that',
     'Arthur',
     'from',
     'the',
     'Court',
     'of',
     'Camelot',
     'is',
     'here',
     '.',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Listen',
     '.',
     'In',
     'order',
     'to',
     'maintain',
     'air',
     '-',
     'speed',
     'velocity',
     ',',
     'a',
     'swallow',
     'needs',
     'to',
     'beat',
     'its',
     'wings',
     'forty',
     '-',
     'three',
     'times',
     'every',
     'second',
     ',',
     'right',
     '?',
     'ARTHUR',
     ':',
     'Please',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Am',
     'I',
     'right',
     '?',
     'ARTHUR',
     ':',
     'I',
     "'",
     'm',
     'not',
     'interested',
     '!',
     'SOLDIER',
     '#',
     '2',
     ':',
     'It',
     'could',
     'be',
     'carried',
     'by',
     'an',
     'African',
     'swallow',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'Oh',
     ',',
     'yeah',
     ',',
     'an',
     'African',
     'swallow',
     'maybe',
     ',',
     'but',
     'not',
     'a',
     'European',
     'swallow',
     '.',
     'That',
     "'",
     's',
     'my',
     'point',
     '.',
     'SOLDIER',
     '#',
     '2',
     ':',
     'Oh',
     ',',
     'yeah',
     ',',
     'I',
     'agree',
     'with',
     'that',
     '.',
     'ARTHUR',
     ':',
     'Will',
     'you',
     'ask',
     'your',
     'master',
     'if',
     'he',
     'wants',
     'to',
     'join',
     'my',
     'court',
     'at',
     'Camelot',
     '?!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'But',
     'then',
     'of',
     'course',
     'a',
     '--',
     'African',
     'swallows',
     'are',
     'non',
     '-',
     'migratory',
     '.',
     'SOLDIER',
     '#',
     '2',
     ':',
     'Oh',
     ',',
     'yeah',
     '...',
     'SOLDIER',
     '#',
     '1',
     ':',
     'So',
     'they',
     'couldn',
     "'",
     't',
     'bring',
     'a',
     'coconut',
     'back',
     'anyway',
     '...',
     '[',
     'clop',
     'clop',
     'clop',
     ']',
     'SOLDIER',
     '#',
     '2',
     ':',
     'Wait',
     'a',
     'minute',
     '!',
     'Supposing',
     'two',
     'swallows',
     'carried',
     'it',
     'together',
     '?',
     'SOLDIER',
     '#',
     '1',
     ':',
     'No',
     ',',
     'they',
     "'",
     'd',
     'have',
     'to',
     'have',
     'it',
     'on',
     'a',
     'line',
     '.',
     'SOLDIER',
     '#',
     '2',
     ':',
     'Well',
     ',',
     'simple',
     '!',
     'They',
     "'",
     'd',
     'just',
     'use',
     'a',
     'strand',
     'of',
     'creeper',
     '!',
     'SOLDIER',
     '#',
     '1',
     ':',
     'What',
     ',',
     'held',
     'under',
     'the',
     'dorsal',
     'guiding',
     'feathers',
     '?',
     'SOLDIER',
     '#',
     '2',
     ':',
     'Well',
     ',',
     'why',
     'not',
     '?',
     'SCENE',
     '2',
     ':',
     '[',
     'thud',
     ']',
     '[',
     'clang',
     ']',
     'CART',
     '-',
     'MASTER',
     ':',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'cough',
     'cough',
     '...]',
     '[',
     'clang',
     ']',
     '[...',
     'cough',
     'cough',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     'Ninepence',
     '.',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     '...',
     '[',
     'rewr',
     '!]',
     '...',
     'your',
     'dead',
     '!',
     '[',
     'rewr',
     '!]',
     '[',
     'clang',
     ']',
     'Bring',
     'out',
     'your',
     'dead',
     '!',
     'CUSTOMER',
     ':',
     'Here',
     "'",
     's',
     'one',
     '.',
     'CART',
     '-',
     'MASTER',
     ':',
     'Ninepence',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     "'",
     'm',
     'not',
     'dead',
     '!',
     'CART',
     '-',
     'MASTER',
     ':',
     'What',
     '?',
     'CUSTOMER',
     ':',
     'Nothing',
     '.',
     'Here',
     "'",
     's',
     'your',
     'ninepence',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     "'",
     'm',
     'not',
     'dead',
     '!',
     'CART',
     '-',
     'MASTER',
     ':',
     "'",
     'Ere',
     '.',
     'He',
     'says',
     'he',
     "'",
     's',
     'not',
     'dead',
     '!',
     'CUSTOMER',
     ':',
     'Yes',
     'he',
     'is',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     "'",
     'm',
     'not',
     '!',
     'CART',
     '-',
     'MASTER',
     ':',
     'He',
     'isn',
     "'",
     't',
     '?',
     'CUSTOMER',
     ':',
     'Well',
     ',',
     'he',
     'will',
     'be',
     'soon',
     '.',
     'He',
     "'",
     's',
     'very',
     'ill',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     "'",
     'm',
     'getting',
     'better',
     '!',
     'CUSTOMER',
     ':',
     'No',
     'you',
     "'",
     're',
     'not',
     '.',
     'You',
     "'",
     'll',
     'be',
     'stone',
     'dead',
     'in',
     'a',
     'moment',
     '.',
     'CART',
     '-',
     'MASTER',
     ':',
     'Oh',
     ',',
     'I',
     'can',
     "'",
     't',
     'take',
     'him',
     'like',
     'that',
     '.',
     'It',
     "'",
     's',
     'against',
     'regulations',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     'don',
     "'",
     't',
     'want',
     'to',
     'go',
     'on',
     'the',
     'cart',
     '!',
     'CUSTOMER',
     ':',
     'Oh',
     ',',
     'don',
     "'",
     't',
     'be',
     'such',
     'a',
     'baby',
     '.',
     'CART',
     '-',
     'MASTER',
     ':',
     'I',
     'can',
     "'",
     't',
     'take',
     'him',
     '.',
     'DEAD',
     'PERSON',
     ':',
     'I',
     'feel',
     'fine',
     '!',
     'CUSTOMER',
     ':',
     'Well',
     ',',
     'do',
     'us',
     'a',
     'favor',
     '.',
     'CART',
     '-',
     'MASTER',
     ':',
     'I',
     'can',
     "'",
     't',
     '.',
     'CUSTOMER',
     ':',
     'Well',
     ',',
     'can',
     'you',
     'hang',
     'around',
     'a',
     'couple',
     'of',
     'minutes',
     '?',
     'He',
     'won',
     "'",
     't',
     'be',
     'long',
     '.',
     'CART',
     '-',
     'MASTER',
     ':',
     'No',
     ',',
     'I',
     "'",
     've',
     'got',
     'to',
     'go',
     'to',
     'the',
     'Robinson',
     "'",
     's',
     '.',
     ...]

Another feature of NLTK are the stopwords that are used in each language that NLTK supports:

```python
english_stopwords = set(nltk.corpus.stopwords.words('english'))
print(english_stopwords)
```

    {'himself', 'we', 'our', 'under', 'here', 'more', 'itself', "haven't", 'couldn', 'will', 'why', 'to', 'who', 'having', 'am', "mustn't", 'up', 'too', "shan't", "that'll", 'does', 'through', "aren't", 'have', 'but', 'when', 'needn', 'y', 'all', 'he', 'shan', 'by', 'from', 't', "mightn't", "shouldn't", "she's", 'wasn', 'no', 'o', 'shouldn', 'once', 'they', 'those', "you're", 'haven', 'll', 'yourself', 'in', 'their', 'if', 'most', "wouldn't", 'or', 'hadn', 'during', "didn't", "doesn't", 'my', 'can', "couldn't", 'these', 'wouldn', 'been', "it's", 'be', 'until', 'you', 'is', 'a', 'own', 'your', 'd', 'them', 'she', 'for', 'hers', 'isn', 'before', 'myself', 'i', 'did', "hasn't", 'mightn', 'there', 'some', 'how', "don't", 'theirs', "wasn't", 'which', 'had', 'further', 'so', 'below', 'hasn', 'are', 'being', 'do', 'it', 'any', 'same', 'its', 'into', 'on', 'whom', 'aren', 'against', 'other', 'doesn', 'while', 'with', "hadn't", 'down', 'above', 'was', 'don', 'each', 'should', 've', 'just', 'themselves', 'now', 'this', 's', 'not', 'where', 'me', 'such', 'at', 'over', 'an', 'won', 'ours', 'nor', 'mustn', 'because', 'ma', "you'd", 'then', 'both', 'between', 'has', 're', "isn't", 'his', "you've", 'ourselves', 'as', 'doing', 'out', 'yours', 'that', 'were', "weren't", 'and', 'herself', 'about', 'very', "should've", "won't", 'what', 'ain', 'weren', 'after', 'only', 'than', 'him', 'of', 'off', 'm', 'few', 'the', 'again', 'didn', 'her', "you'll", 'yourselves', "needn't"}

__POS-tagging__ is another method of describing our text. For each tokenized word we can obtain it's __Part Of Speech__. Those informations are frequently used throughout more advanced machine learning methods.

Up until now everything was easy, fortunately this one is no exception.

```python
# we have already imported nltk.tokenize.word_tokenizer

nltk.download('averaged_perceptron_tagger')

words = word_tokenize(
    "Another text. You know, this is the hardest part, coming up with all those texts. "
    "Lorem Ipsum or some random stuff is pretty boring IMO. "
    "You may feel like somebody didn't care (or at least I do)."
    "Or maybe it's just an act? I will not address this question."
)

nltk.pos_tag(words)
```

    [nltk_data] Downloading package averaged_perceptron_tagger to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package averaged_perceptron_tagger is already up-to-
    [nltk_data]       date!

    [('Another', 'DT'),
     ('text', 'NN'),
     ('.', '.'),
     ('You', 'PRP'),
     ('know', 'VBP'),
     (',', ','),
     ('this', 'DT'),
     ('is', 'VBZ'),
     ('the', 'DT'),
     ('hardest', 'JJS'),
     ('part', 'NN'),
     (',', ','),
     ('coming', 'VBG'),
     ('up', 'RP'),
     ('with', 'IN'),
     ('all', 'PDT'),
     ('those', 'DT'),
     ('texts', 'NNS'),
     ('.', '.'),
     ('Lorem', 'NNP'),
     ('Ipsum', 'NNP'),
     ('or', 'CC'),
     ('some', 'DT'),
     ('random', 'JJ'),
     ('stuff', 'NN'),
     ('is', 'VBZ'),
     ('pretty', 'JJ'),
     ('boring', 'JJ'),
     ('IMO', 'NNP'),
     ('.', '.'),
     ('You', 'PRP'),
     ('may', 'MD'),
     ('feel', 'VB'),
     ('like', 'IN'),
     ('somebody', 'NN'),
     ('did', 'VBD'),
     ("n't", 'RB'),
     ('care', 'VB'),
     ('(', '('),
     ('or', 'CC'),
     ('at', 'IN'),
     ('least', 'JJS'),
     ('I', 'PRP'),
     ('do', 'VBP'),
     (')', ')'),
     ('.Or', 'VB'),
     ('maybe', 'RB'),
     ('it', 'PRP'),
     ("'s", 'VBZ'),
     ('just', 'RB'),
     ('an', 'DT'),
     ('act', 'NN'),
     ('?', '.'),
     ('I', 'PRP'),
     ('will', 'MD'),
     ('not', 'RB'),
     ('address', 'VB'),
     ('this', 'DT'),
     ('question', 'NN'),
     ('.', '.')]

Look at `act` and `address` towards the end of output.

POS can be used to dismabiguate word meaning, `act` can be both noun (NN) and verb (VB), same goes for address.

This tokenizer is __based on simple one layer neural network__ hence it takes context into account (words before and after an act).

Context (N words before and after certain word) is called __N-gram__ in Machine Learning and we will make use of it more later in this course.

<ADD N-GRAM PHOTO>

This is more sophisticated approach and __should be__ used when more abstract reasoning is needed (like word disambiguation).

With __NLTK__ we can create and train our own taggers, or choose a pre-made one and train is as seen below (this one takes the next word as it's context).

```python
import nltk
from nltk.corpus import brown
nltk.download("brown")

brown_tagged_sents = brown.tagged_sents(categories="news")
brown_sents = brown.sents(categories="news")
unigram_tagger = nltk.BigramTagger(brown_tagged_sents)
unigram_tagger.tag(brown_sents[2007])
```

    [nltk_data] Downloading package brown to
    [nltk_data]     /home/kprzystalski/nltk_data...
    [nltk_data]   Package brown is already up-to-date!

    [('Various', 'JJ'),
     ('of', 'IN'),
     ('the', 'AT'),
     ('apartments', 'NNS'),
     ('are', 'BER'),
     ('of', 'IN'),
     ('the', 'AT'),
     ('terrace', 'NN'),
     ('type', 'NN'),
     (',', ','),
     ('being', 'BEG'),
     ('on', 'IN'),
     ('the', 'AT'),
     ('ground', 'NN'),
     ('floor', 'NN'),
     ('so', 'CS'),
     ('that', 'CS'),
     ('entrance', 'NN'),
     ('is', 'BEZ'),
     ('direct', 'JJ'),
     ('.', '.')]

### Unicode

Each alphabet is different and some languages use letter that are not used in any other language. Unicode allows use to standardize the text. Let's see an of some german and portugese text below.

```python
sample = """Minderjährige Schülerinnen. O português é uma língua romântica"""

type(sample)
```

    str

If we convert it to ASCII it will look as following:

```python
ascii(sample)
```

    "'Minderj\\xe4hrige Sch\\xfclerinnen. O portugu\\xeas \\xe9 uma l\\xedngua rom\\xe2ntica'"

It is not what we expected. It's hard to work with such a text. We can go a step further and encode the string to be a unicode encoded one:

```python
sample.encode('utf8')
```

    b'Minderj\xc3\xa4hrige Sch\xc3\xbclerinnen. O portugu\xc3\xaas \xc3\xa9 uma l\xc3\xadngua rom\xc3\xa2ntica'

We could also ignore the ASCII characters that we cannot do anything with in the further processing:

```python
sample.encode('ascii', 'ignore')
```

    b'Minderjhrige Schlerinnen. O portugus  uma lngua romntica'

Now we have all letter that make sense, but we have text that does not make any sense anymore. To solve it, we need to normalize it and only after the normalization remove the ascii signs.

```python
import unicodedata

unicodedata.normalize('NFKD', sample).encode('ascii','ignore')
```

    b'Minderjahrige Schulerinnen. O portugues e uma lingua romantica'

More about [Unicode normalization forms](http://unicode.org/reports/tr15/)

### Lemmatization

Lemmatization is a process of getting one word for many forms of the word.

Let's see an example:

```python
from nltk.stem import WordNetLemmatizer

wordnet_lemmatizer = WordNetLemmatizer()

print(wordnet_lemmatizer.lemmatize('do',pos='v'))
print(wordnet_lemmatizer.lemmatize('does',pos='v'))
print(wordnet_lemmatizer.lemmatize('doing',pos='v'))
```

    do
    do
    do

We can set the main part of speech as one of the following:

ADJ, ADJ_SAT, ADV, NOUN, VERB = 'a', 's', 'r', 'n', 'v'

```python
wordnet_lemmatizer.lemmatize('are',pos='v')
```

    'be'

### Stemming

Stemming is similar to lemmatization, but the main difference is that is just reduce the word to it root. It gives in many cases different results than lemmatization as the second solution is based on part of speech.

```python
from nltk import PorterStemmer, LancasterStemmer, word_tokenize
from nltk.stem.snowball import SnowballStemmer

sample = "This is a new training about machine learning usage for chatbots"

tokens = word_tokenize(sample)

porter = PorterStemmer()
p_stem = [porter.stem(t) for t in tokens]
print(p_stem)

lancaster = LancasterStemmer()
l_stem = [lancaster.stem(t) for t in tokens]
print(l_stem)

snowball = SnowballStemmer('english')
s_stem = [snowball.stem(t) for t in tokens]
print(s_stem)
```

    ['thi', 'is', 'a', 'new', 'train', 'about', 'machin', 'learn', 'usag', 'for', 'chatbot']
    ['thi', 'is', 'a', 'new', 'train', 'about', 'machin', 'learn', 'us', 'for', 'chatbot']
    ['this', 'is', 'a', 'new', 'train', 'about', 'machin', 'learn', 'usag', 'for', 'chatbot']

As per usual there are other stemmers and lemmatizers available in NLTK.
Some
of them may be faster (PorterStemmer), but Snowball is considered de-facto
standard.

A few traits of each should be noticed:
- Stemming is faster (it
doesn't have to consult dictionary and complicated
morphological rules).
-
Stemming may not produce a dictionary word, see `studi` above.
- Lemmatization
produces smaller set of words. It is useful as we do not have to keep
track of
all the different form of word (running, runner, runs etc.). More memory
efficient.
- Lemmatization is not as crude, when it does not find the lemma it
returns the original
form. It __may__ produce more words this way, depends on
the kind of text we are
processing.

### Sentence extraction

In this section we show some features of SpaCy. One of the most commonly used is the sentence extraction. An example of Trump speech divided into sentences can be found below.

```python
import spacy

file = open("../datasets/trump.txt", "r",encoding='utf-8')
trump = file.read()

nlp = spacy.load("en_core_web_sm")
doc = nlp(trump)

for span in doc.sents:
    print("> ", span)
```

    >  Thank you very much.
    >  Mr. Speaker, Mr. Vice President, Members of Congress, the First Lady of the United States, and citizens of America: Tonight, as we mark the conclusion of our celebration of Black History Month, we are reminded of our Nation's path towards civil rights and the work that still remains to be done.
    >  Recent threats targeting Jewish community centers and vandalism of Jewish cemeteries, as well as last week's shooting in Kansas City, remind us that while we may be a nation divided on policies, we are a country that stands united in condemning hate and evil in all of its very ugly forms.
    >

    >  Each American generation passes the torch of truth, liberty, and justice in an unbroken chain, all the way down to the present.
    >  That torch is now in our hands, and we will use it to light up the world.
    >  I am here tonight to deliver a message of unity and strength, and it is a message deeply delivered from my heart.
    >  A new chapter of American greatness is now beginning.
    >  A new national pride is sweeping across our Nation.
    >  And a new surge of optimism is placing impossible dreams firmly within our grasp.
    >

    What we are witnessing today is the renewal of the American spirit.
    >  Our allies will find that America is once again ready to lead.
    >  All the nations of the world—friend or foe—will find that America is strong, America is proud, and America is free.
    >

    >  In 9 years, the United States will celebrate the 250th anniversary of our founding: 250 years since the day we declared our independence.
    >  It will be one of the great milestones in the history of the world.
    >  But what will America look like as we reach our 250th year?
    >  What kind of country will we leave for our children?
    >

    I will not allow the mistakes of recent decades past to define the course of our future.
    >  For too long, we've watched our middle class shrink as we've exported our jobs and wealth to foreign countries.
    >  We've financed and built one global project after another, but ignored the fates of our children in the inner cities of Chicago, Baltimore, Detroit, and so many other places throughout our land.
    >

    We've defended the borders of other nations, while leaving our own borders wide open for anyone to cross and for drugs to pour in at a now unprecedented rate.
    >  And we've spent trillions and trillions of dollars overseas, while our infrastructure at home has so badly crumbled.
    >

    Then, in 2016, the Earth shifted beneath our feet.
    >  The rebellion started as a quiet protest, spoken by families of all colors and creeds, families who just wanted a fair shot for their children and a fair hearing for their concerns.
    >

    >  But then the quiet voices became a loud chorus, as thousands of citizens now spoke out together, from cities small and large, all across our country.
    >  Finally, the chorus became an earthquake, and the people turned out by the tens of millions, and they were all united by one very simple, but crucial demand: that America must put its own citizens first.
    >  Because only then can we truly make America great again.
    >

    Dying industries will come roaring back to life.
    >  Heroic veterans will get the care they so desperately need.
    >  Our military will be given the resources its brave warriors so richly deserve.
    >  Crumbling infrastructure will be replaced with new roads, bridges, tunnels, airports, and railways gleaming across our very, very beautiful land.
    >  Our terrible drug epidemic will slow down and, ultimately, stop.
    >  And our neglected inner cities will see a rebirth of hope, safety, and opportunity.
    >  Above all else, we will keep our promises to the American people.
    >  [Applause] Thank you.
    >

    It's been a little over a month since my Inauguration, and I want to take this moment to update the Nation on the progress I've made in keeping those promises.
    >

    >  Since my election, Ford, Fiat Chrysler, General Motors, Sprint, Softbank, Lockheed, Intel, Walmart, and many others have announced that they will invest billions and billions of dollars in the United States and will create tens of thousands of new American jobs.
    >

    The stock market has gained almost $3 trillion in value since the election on November 8—a record.
    >  We've saved taxpayers hundreds of millions of dollars by bringing down the price of fantastic—and it is a fantastic—new F-35 jet fighter, and we'll be saving billions more on contracts all across our Government.
    >  We have placed a hiring freeze on nonmilitary and nonessential Federal workers.
    >

    We have begun to drain the swamp of government corruption by imposing a 5-year ban on lobbying by executive branch officials and a lifetime ban—[applause]—thank you.
    >  Thank you.
    >  And a lifetime ban on becoming lobbyists for a foreign government.
    >

    We have undertaken a historic effort to massively reduce job-crushing regulations, creating a deregulation Task Force inside of every Government agency.
    >  And we're imposing a new rule which mandates that for every one new regulation, two old regulations must be eliminated.
    >  We're going to stop the regulations that threaten the future and livelihood of our great coal miners.
    >

    We have cleared the way for the construction of the Keystone and Dakota Access pipelines, thereby creating tens of thousands of jobs.
    >  And I've issued a new directive that new American pipelines be made with American steel.
    >

    We have withdrawn the United States from the job-killing Trans-Pacific Partnership.
    >  And with the help of Prime Minister Justin Trudeau, we have formed a council with our neighbors in Canada to help ensure that women entrepreneurs have access to the networks, markets, and capital they need to start a business and live out their financial dreams.
    >

    To protect our citizens, I have directed the Department of Justice to form a Task Force on Reducing Violent Crime.
    >  I have further ordered the Departments of Homeland Security and Justice, along with the Department of State and the Director of National Intelligence, to coordinate an aggressive strategy to dismantle the criminal cartels that have spread all across our Nation.
    >  We will stop the drugs from pouring into our country and poisoning our youth, and we will expand treatment for those who have become so badly addicted.
    >

    >  At the same time, my administration has answered the pleas of the American people for immigration enforcement and border security.
    >  By finally enforcing our immigration laws, we will raise wages, help the unemployed, save billions and billions of dollars, and make our communities safer for everyone.
    >  We want all Americans to succeed, but that can't happen in an environment of lawless chaos.
    >  We must restore integrity and the rule of law at our borders.
    >

    >  For that reason, we will soon begin the construction of a great, great wall along our southern border.
    >  As we speak tonight, we are removing gang members, drug dealers, and criminals that threaten our communities and prey on our very innocent citizens.
    >  Bad ones are going out as I speak, and as I've promised throughout the campaign.
    >

    >  To any in Congress who do not believe we should enforce our laws, I would ask you this one question: What would you say to the American family that loses their jobs, their income, or their loved one because America refused to uphold its laws and defend its borders?
    >

    Our obligation is to serve, protect, and defend the citizens of the United States.
    >  We are also taking strong measures to protect our Nation from radical Islamic terrorism.
    >  According to data provided by the Department of Justice, the vast majority of individuals convicted of terrorism and terrorism-related offenses since 9/11 came here from outside of our country.
    >  We have seen the attacks at home, from Boston to San Bernardino to the Pentagon, and, yes, even the World Trade Center.
    >

    We have seen the attacks in France, in Belgium, in Germany, and all over the world.
    >  It is not compassionate, but reckless to allow uncontrolled entry from places where proper vetting cannot occur.
    >  Those given the high honor of admission to the United States should support this country and love its people and its values.
    >  We cannot allow a beachhead of terrorism to form inside America.
    >  We cannot allow our Nation to become a sanctuary for extremists.
    >

    >  That is why my administration has been working on improved vetting procedures, and we will shortly take new steps to keep our Nation safe and to keep those out who will do us harm.
    >

    As promised, I directed the Department of Defense to develop a plan to demolish and destroy ISIS, a network of lawless savages that have slaughtered Muslims and Christians, and men and women and children of all faiths and all beliefs.
    >  We will work with our allies, including our friends and allies in the Muslim world, to extinguish this vile enemy from our planet.
    >

    I have also imposed new sanctions on entities and individuals who support Iran's ballistic missile program and reaffirmed our unbreakable alliance with the State of Israel.
    >

    >  Finally, I have kept my promise to appoint a Justice to the United States Supreme Court, from my list of 20 judges, who will defend our Constitution.
    >

    >  I am greatly honored to have Maureen Scalia with us in the gallery tonight.
    >  Thank you, Maureen.
    >  Her late, great husband, Antonin Scalia, will forever be a symbol of American justice.
    >  To fill his seat, we have chosen Judge Neil Gorsuch, a man of incredible skill and deep devotion to the law.
    >  He was confirmed unanimously by the Court of Appeals, and I am asking the Senate to swiftly approve his nomination.
    >

    >  Tonight, as I outline the next steps we must take as a country, we must honestly acknowledge the circumstances we inherited.
    >  Ninety-four million Americans are out of the labor force.
    >  Over 43 million people are now living in poverty, and over 43 million Americans are on food stamps.
    >  More than 1 in 5 people in their prime working years are not working.
    >  We have the worst financial recovery in 65 years.
    >  In the last 8 years, the past administration has put on more new debt than nearly all of the other Presidents combined.
    >

    We've lost more than one-fourth of our manufacturing jobs since NAFTA was approved, and we've lost 60,000 factories since China joined the World Trade Organization in 2001.
    >  Our trade deficit in goods with the world last year was nearly $800 billion dollars.
    >  And overseas we have inherited a series of tragic foreign policy disasters.
    >  Solving these and so many other pressing problems will require us to work past the differences of party.
    >  It will require us to tap into the American spirit that has overcome every challenge throughout our long and storied history.
    >  But to accomplish our goals at home and abroad, we must restart the engine of the American economy, making it easier for companies to do business in the United States, and much, much harder for companies to leave our country.
    >

    >  Right now American companies are taxed at one of the highest rates anywhere in the world.
    >  My economic team is developing historic tax reform that will reduce the tax rate on our companies so they can compete and thrive anywhere and with anyone.
    >  It will be a big, big cut.
    >

    At the same time, we will provide massive tax relief for the middle class.
    >  We must create a level playing field for American companies and our workers—have to do it.
    >  Currently, when we ship products out of America, many other countries make us pay very high tariffs and taxes.
    >  But when foreign companies ship their products into America, we charge them nothing, or almost nothing.
    >

    I just met with officials and workers from a great American company, Harley-Davidson.
    >  In fact, they proudly displayed five of their magnificent motorcycles, made in the U.S.A., on the front lawn of the White House.
    >  [Laughter]
    >  And they wanted me to ride one, and I said, "No, thank you."
    >  [Laughter]

    At our meeting, I asked them, how are you doing, how is business?
    >  They said that it's good.
    >  I asked them further, how are you doing with other countries, mainly international sales?
    >  They told me—without even complaining, because they have been so mistreated for so long that they've become used to it—that it's very hard to do business with other countries because they tax our goods at such a high rate.
    >  They said that in the case of another country, they taxed their motorcycles at 100 percent.
    >  They weren't even asking for a change.
    >  But I am.
    >

    I believe strongly in free trade, but it also has to be fair trade.
    >  It's been a long time since we had fair trade.
    >  The first Republican President, Abraham Lincoln, warned that the "abandonment of the protective policy by the American Government will produce want and ruin among our people."
    >  Lincoln was right, and it's time we heeded his advice and his words.
    >  I am not going to let America and its great companies and workers be taken advantage of us any longer.
    >  They have taken advantage of our country.
    >  No longer.
    >

    I am going to bring back millions of jobs.
    >  Protecting our workers also means reforming our system of legal immigration.
    >  The current, outdated system depresses wages for our poorest workers and puts great pressure on taxpayers.
    >  Nations around the world like Canada, Australia, and many others, have a merit-based immigration system.
    >  It's a basic principle that those seeking to enter a country ought to be able to support themselves financially.
    >  Yet, in America, we do not enforce this rule, straining the very public resources that our poorest citizens rely upon.
    >  According to the National Academy of Sciences, our current immigration system costs American taxpayers many billions of dollars a year.
    >

    Switching away from this current system of lower skilled immigration, and instead adopting a merit-based system, we will have so many more benefits.
    >  It will save countless dollars, raise workers' wages, and help struggling families—including immigrant families—enter the middle class.
    >  And they will do it quickly, and they will be very, very happy, indeed.
    >

    I believe that real and positive immigration reform is possible, as long as we focus on the following goals: to improve jobs and wages for Americans, to strengthen our Nation's security, and to restore respect for our laws.
    >  If we are guided by the wellbeing of American citizens, then I believe Republicans and Democrats can work together to achieve an outcome that has eluded our country for decades.
    >

    Another Republican President, Dwight D. Eisenhower, initiated the last truly great national infrastructure program—the building of the Interstate Highway System.
    >  The time has come for a new program of national rebuilding.
    >  America has spent approximately $6 trillion in the Middle East; all the while, our infrastructure at home is crumbling.
    >  With this $6 trillion, we could have rebuilt our country twice, and maybe even three times if we had people who had the ability to negotiate.
    >  [Laughter]

    To launch our national rebuilding, I will be asking Congress to approve legislation that produces a $1 trillion investment in infrastructure of the United States—financed through both public and private capital—creating millions of new jobs.
    >  This effort will be guided by two core principles: buy American and hire American.
    >

    >  Tonight I am also calling on this Congress to repeal and replace Obamacare with reforms that expand choice, increase access, lower costs, and at the same time, provide better health care.
    >

    Mandating every American to buy Government-approved health insurance was never the right solution for our country.
    >  The way to make health insurance available to everyone is to lower the cost of health insurance, and that is what we are going do.
    >

    Obamacare premiums nationwide have increased by double and triple digits.
    >  As an example, Arizona went up 116 percent last year alone.
    >  Governor Matt Bevin of Kentucky just said Obamacare is failing in his State—the State of Kentucky—and it's unsustainable and collapsing.
    >

    One-third of the counties have only one insurer, and they are losing them fast.
    >  They are losing them so fast.
    >  They are leaving, and many Americans have no choice at all.
    >  There's no choice left.
    >  Remember when you were told that you could keep your doctor and keep your plan?
    >  We now know that all of those promises have been totally broken.
    >  Obamacare is collapsing, and we must act decisively to protect all Americans.

    >  Action is not a choice, it is a necessity.
    >  So I am calling on all Democrats and Republicans in Congress to work with us to save Americans from this imploding Obamacare disaster.
    >

    >  Here are the principles that should guide the Congress as we move to create a better health care system for all Americans:

    First, we should ensure that Americans with preexisting conditions have access to coverage, and that we have a stable transition for Americans currently enrolled in the health care exchanges.
    >

    >  Secondly, we should help Americans purchase their own coverage through the use of tax credits and expanded health savings accounts, but it must be the plan they want, not the plan forced on them by our Government.
    >

    >  Thirdly, we should give our State Governors the resources and flexibility they need with Medicaid to make sure no one is left out.
    >

    Fourth, we should implement legal reforms that protect patients and doctors from unnecessary costs that drive up the price of insurance and work to bring down the artificially high price of drugs and bring them down immediately.
    >  And finally, the time has come to give Americans the freedom to purchase health insurance across State lines, which will create a truly competitive national marketplace that will bring costs way down and provide far better care.
    >  So important.
    >

    Everything that is broken in our country can be fixed.
    >  Every problem can be solved.
    >  And every hurting family can find healing and hope.
    >

    Our citizens deserve this and so much more, so why not join forces and finally get the job done, and get it done right?
    >  On this and so many other things, Democrats and Republicans should get together and unite for the good of our country and for the good of the American people.
    >

    My administration wants to work with members of both parties to make childcare accessible and affordable; to help ensure new parents that they have paid family leave; to invest in women's health; and to promote clean air and clean water; and to rebuild our military and our infrastructure.
    >

    True love for our people requires us to find common ground, to advance the common good, and to cooperate on behalf of every American child who deserves a much brighter future.
    >

    An incredible young woman is with us this evening, who should serve as an inspiration to us all.
    >  Today is Rare Disease Day, and joining us in the gallery is a rare disease survivor, Megan Crowley.
    >

    Megan was diagnosed with Pompe disease, a rare and serious illness, when she was 15 months old.
    >  She was not expected to live past 5.
    >  On receiving this news, Megan's dad John fought with everything he had to save the life of his precious child.
    >  He founded a company to look for a cure and helped develop the drug that saved Megan's life.
    >  Today she is 20 years old and a sophomore at Notre Dame.
    >

    Megan's story is about the unbounded power of a father's love for a daughter.
    >  But our slow and burdensome approval process at the Food and Drug Administration keeps too many advances, like the one that saved Megan's life, from reaching those in need.
    >  If we slash the restraints, not just at the FDA, but across our Government, then we will be blessed with far more miracles just like Megan.
    >  In fact, our children will grow up in a nation of miracles.
    >

    >  But to achieve this future, we must enrich the mind and the souls of every American child.
    >  Education is the civil rights issue of our time.
    >  I am calling upon members of both parties to pass an education bill that funds school choice for disadvantaged youth, including millions of African American and Latino children.
    >  These families should be free to choose the public, private, charter, magnet, religious, or home school that is right for them.
    >

    >  Joining us tonight in the gallery is a remarkable woman, Denisha Merriweather.
    >  As a young girl, Denisha struggled in school and failed third grade twice.
    >  But then, she was able to enroll in a private center for learning—great learning center—with the help of a tax credit and a scholarship program.
    >

    Today, she is the first in her family to graduate, not just from high school, but from college.
    >  Later this year she will get her master's degree in social work.
    >  We want all children to be able to break the cycle of poverty just like Denisha.
    >

    >  But to break the cycle of poverty, we must also break the cycle of violence.
    >  The murder rate in 2015 experienced its largest single-year increase in nearly half a century.
    >  In Chicago, more than 4,000 people were shot last year alone, and the murder rate so far this year has been even higher.
    >  This is not acceptable in our society.
    >

    >  Every American child should be able to grow up in a safe community, to attend a great school, and to have access to a high-paying job.
    >  But to create this future, we must work with, not against—not against—the men and women of law enforcement.
    >  We must build bridges of cooperation and trust, not drive the wedge of disunity, and really, it's what it is—division.
    >  It's pure, unadulterated division.
    >  We have to unify.
    >

    Police and sheriffs are members of our community.
    >  They're friends and neighbors, they're mothers and fathers, sons and daughters, and they leave behind loved ones every day who worry about whether or not they'll come home safe and sound.
    >  We must support the incredible men and women of law enforcement.
    >

    >  And we must support the victims of crime.
    >  I have ordered the Department of Homeland Security to create an office to serve American victims.
    >  The office is called VOICE:
    >  Victims of Immigration Crime Engagement.
    >  We are providing a voice to those who have been ignored by our media and silenced by special interests.
    >  Joining us in the audience tonight are four very brave Americans whose Government failed them.
    >  Their names are Jamiel Shaw, Susan Oliver, Jenna Oliver, and Jessica Davis.
    >

    Jamiel's 17-year-old son was viciously murdered by an illegal immigrant gang member who had just been released from prison.
    >  Jamiel Shaw, Jr. was an incredible young man, with unlimited potential, who was getting ready to go to college where he would have excelled as a great college quarterback.
    >  But he never got the chance.
    >  His father, who is in the audience tonight, has become a very good friend of mine.
    >  Jamiel, thank you.
    >  Thank you.
    >

    Also with us are Susan Oliver and Jessica Davis.
    >  Their husbands, Deputy Sheriff Danny Oliver and Detective Michael Davis, were slain in the line of duty in California.
    >  They were pillars of their community.
    >  These brave men were viciously gunned down by an illegal immigrant with a criminal record and two prior deportations.
    >  Should have never been in our country.
    >

    >  Sitting with Susan is her daughter, Jenna.
    >  Jenna, I want you to know that your father was a hero, and that tonight you have the love of an entire country supporting you and praying for you.
    >

    >  To Jamiel, Jenna, Susan, and Jessica: I want you to know that we will never stop fighting for justice.
    >  Your loved ones will never, ever be forgotten.
    >  We will always honor their memory.
    >

    Finally, to keep America safe, we must provide the men and women of the United States military with the tools they need to prevent war.
    >  If they must, they have to fight and they only have to win.
    >

    I am sending Congress a budget that rebuilds the military, eliminates the defense sequester, and calls for one of the largest increases in national defense spending in American history.
    >  My budget will also increase funding for our veterans.
    >  Our veterans have delivered for this Nation, and now we must deliver for them.
    >

    >  The challenges we face as a nation are great, but our people are even greater.
    >  And none are greater or are braver than those who fight for America in uniform.
    >

    We are blessed to be joined tonight by Carryn Owens, the widow of U.S. Navy Special Operator, Senior Chief William "Ryan" Owens.
    >  Ryan died as he lived: a warrior and a hero, battling against terrorism and securing our Nation.
    >  I just spoke to our great General Mattis, just now, who reconfirmed that—and I quote—"Ryan was a part of a highly successful raid that generated large amounts of vital intelligence that will lead to many more victories in the future against our enemy."
    >  Ryan's legacy is etched into eternity.
    >  Thank you.
    >  [Applause] And Ryan is looking down, right now—you know that—and he is very happy because I think he just broke a record.
    >  [Laughter]

    For as the Bible teaches us, there is no greater act of love than to lay down one's life for one's friends.
    >  Ryan laid down his life for his friends, for his country, and for our freedom.
    >  And we will never forget Ryan.
    >

    >  To those allies who wonder what kind of a friend America will be, look no further than the heroes who wear our uniform.
    >  Our foreign policy calls for a direct, robust, and meaningful engagement with the world.
    >  It is American leadership based on vital security interests that we share with our allies all across the globe.
    >

    We strongly support NATO, an alliance forged through the bonds of two world wars that dethroned fascism, and a cold war, and defeated communism.
    >

    >  But our partners must meet their financial obligations.
    >  And now, based on our very strong and frank discussions, they are beginning to do just that.
    >  In fact, I can tell you, the money is pouring in.
    >  Very nice.
    >  We expect our partners—whether in NATO, the Middle East, or in the Pacific—to take a direct and meaningful role in both strategic and military operations, and pay their fair share of the cost.
    >  Have to do that.
    >

    We will respect historic institutions, but we will respect the foreign rights of all nations, and they have to respect our rights as a nation also.
    >  Free nations are the best vehicle for expressing the will of the people, and America respects the right of all nations to chart their own path.
    >  My job is not to represent the world.
    >  My job is to represent the United States of America.
    >

    >  But we know that America is better off when there is less conflict, not more.
    >  We must learn from the mistakes of the past.
    >  We have seen the war and the destruction that have ravaged and raged throughout the world—all across the world.
    >  The only long-term solution for these humanitarian disasters, in many cases, is to create the conditions where displaced persons can safely return home and begin the long, long process of rebuilding.
    >

    America is willing to find new friends and to forge new partnerships where shared interests align.
    >  We want harmony and stability, not war and conflict.
    >  We want peace, wherever peace can be found.
    >

    America is friends today with former enemies.
    >  Some of our closest allies, decades ago, fought on the opposite side of these terrible, terrible wars.
    >  This history should give us all faith in the possibilities for a better world.
    >  Hopefully, the 250th year for America will see a world that is more peaceful, more just, and more free.
    >

    >  On our 100th anniversary, in 1876, citizens from across our Nation came to Philadelphia to celebrate America's centennial.
    >  At that celebration, the country's builders and artists and inventors showed off their wonderful creations.
    >  Alexander Graham Bell displayed his telephone for the first time.
    >  Remington unveiled the first typewriter.
    >  An early attempt was made at electric light.
    >  Thomas Edison showed an automatic telegraph and an electric pen.
    >  Imagine the wonders our country could know in America's 250th year.
    >  Think of the marvels we can achieve if we simply set free the dreams of our people.
    >  Cures to the illnesses that have always plagued us are not too much to hope.
    >  American footprints on distant worlds are not too big a dream.
    >  Millions lifted from welfare to work is not too much to expect.
    >  And streets where mothers are safe from fear, schools where children learn in peace, and jobs where Americans prosper and grow are not too much to ask.
    >

    When we have all of this, we will have made America greater than ever before—for all Americans.
    >  This is our vision.
    >  This is our mission.
    >  But we can only get there together.
    >  We are one people with one destiny.
    >  We all bleed the same blood.
    >  We all salute the same great American flag.
    >  And we all are made by the same God.
    >

    When we fulfill this vision, when we celebrate our 250 years of glorious freedom, we will look back on tonight as when this new chapter of American greatness began.
    >  The time for small thinking is over.
    >  The time for trivial fights is behind us.
    >  We just need the courage to share the dreams that fill our hearts, the bravery to express the hopes that stir our souls, and the confidence to turn those hopes and those dreams into action.
    >

    >  From now on, America will be empowered by our aspirations, not burdened by our fears; inspired by the future, not bound by failures of the past; and guided by our vision, not blinded by our doubts.
    >

    I am asking all citizens to embrace this renewal of the American spirit.
    >  I am asking all Members of Congress to join me in dreaming big and bold, and daring things for our country.
    >  I am asking everyone watching tonight to seize this moment.
    >  Believe in yourselves, believe in your future, and believe, once more, in America.
    >

    Thank you, God bless you, and God bless the United States.

Each sentence can next be tokenized and we can get a tag and pos of it.

```python
for span in doc.sents:
    for i in range(span.start, span.end):
        token = doc[i]
        print(i, token.text, token.tag_, token.pos_)
```

    0 Thank VBP VERB
    1 you PRP PRON
    2 very RB ADV
    3 much RB ADV
    4 . . PUNCT
    5 Mr. NNP PROPN
    6 Speaker NNP PROPN
    7 , , PUNCT
    8 Mr. NNP PROPN
    9 Vice NNP PROPN
    10 President NNP PROPN
    11 , , PUNCT
    12 Members NNS NOUN
    13 of IN ADP
    14 Congress NNP PROPN
    15 , , PUNCT
    16 the DT DET
    17 First NNP PROPN
    18 Lady NNP PROPN
    19 of IN ADP
    20 the DT DET
    21 United NNP PROPN
    22 States NNP PROPN
    23 , , PUNCT
    24 and CC CCONJ
    25 citizens NNS NOUN
    26 of IN ADP
    27 America NNP PROPN
    28 : : PUNCT
    29 Tonight NN NOUN
    30 , , PUNCT
    31 as IN ADP
    32 we PRP PRON
    33 mark VBP VERB
    34 the DT DET
    35 conclusion NN NOUN
    36 of IN ADP
    37 our PRP$ PRON
    38 celebration NN NOUN
    39 of IN ADP
    40 Black NNP PROPN
    41 History NNP PROPN
    42 Month NNP PROPN
    43 , , PUNCT
    44 we PRP PRON
    45 are VBP AUX
    46 reminded VBN VERB
    47 of IN ADP
    48 our PRP$ PRON
    49 Nation NN NOUN
    50 's POS PART
    51 path NN NOUN
    52 towards IN ADP
    53 civil JJ ADJ
    54 rights NNS NOUN
    55 and CC CCONJ
    56 the DT DET
    57 work NN NOUN
    58 that WDT DET
    59 still RB ADV
    60 remains VBZ VERB
    61 to TO PART
    62 be VB AUX
    63 done VBN VERB
    64 . . PUNCT
    65 Recent JJ ADJ
    66 threats NNS NOUN
    67 targeting VBG VERB
    68 Jewish JJ ADJ
    69 community NN NOUN
    70 centers NNS NOUN
    71 and CC CCONJ
    72 vandalism NN NOUN
    73 of IN ADP
    74 Jewish JJ ADJ
    75 cemeteries NNS NOUN
    76 , , PUNCT
    77 as RB ADV
    78 well RB ADV
    79 as IN ADP
    80 last JJ ADJ
    81 week NN NOUN
    82 's POS PART
    83 shooting NN NOUN
    84 in IN ADP
    85 Kansas NNP PROPN
    86 City NNP PROPN
    87 , , PUNCT
    88 remind VB VERB
    89 us PRP PRON
    90 that IN SCONJ
    91 while IN SCONJ
    92 we PRP PRON
    93 may MD AUX
    94 be VB VERB
    95 a DT DET
    96 nation NN NOUN
    97 divided VBN VERB
    98 on IN ADP
    99 policies NNS NOUN
    100 , , PUNCT
    101 we PRP PRON
    102 are VBP AUX
    103 a DT DET
    104 country NN NOUN
    105 that WDT DET
    106 stands VBZ VERB
    107 united JJ ADJ
    108 in IN ADP
    109 condemning VBG VERB
    110 hate NN NOUN
    111 and CC CCONJ
    112 evil NN NOUN
    113 in IN ADP
    114 all DT DET
    115 of IN ADP
    116 its PRP$ PRON
    117 very RB ADV
    118 ugly JJ ADJ
    119 forms NNS NOUN
    120 . . PUNCT
    121
     _SP SPACE
    122 Each DT DET
    123 American JJ ADJ
    124 generation NN NOUN
    125 passes VBZ VERB
    126 the DT DET
    127 torch NN NOUN
    128 of IN ADP
    129 truth NN NOUN
    130 , , PUNCT
    131 liberty NN NOUN
    132 , , PUNCT
    133 and CC CCONJ
    134 justice NN NOUN
    135 in IN ADP
    136 an DT DET
    137 unbroken JJ ADJ
    138 chain NN NOUN
    139 , , PUNCT
    140 all PDT DET
    141 the DT DET
    142 way NN NOUN
    143 down RB ADV
    144 to IN ADP
    145 the DT DET
    146 present NN NOUN
    147 . . PUNCT
    148 That DT DET
    149 torch NN NOUN
    150 is VBZ AUX
    151 now RB ADV
    152 in IN ADP
    153 our PRP$ PRON
    154 hands NNS NOUN
    155 , , PUNCT
    156 and CC CCONJ
    157 we PRP PRON
    158 will MD AUX
    159 use VB VERB
    160 it PRP PRON
    161 to TO PART
    162 light VB VERB
    163 up RP ADP
    164 the DT DET
    165 world NN NOUN
    166 . . PUNCT
    167 I PRP PRON
    168 am VBP AUX
    169 here RB ADV
    170 tonight NN NOUN
    171 to TO PART
    172 deliver VB VERB
    173 a DT DET
    174 message NN NOUN
    175 of IN ADP
    176 unity NN NOUN
    177 and CC CCONJ
    178 strength NN NOUN
    179 , , PUNCT
    180 and CC CCONJ
    181 it PRP PRON
    182 is VBZ VERB
    183 a DT DET
    184 message NN NOUN
    185 deeply RB ADV
    186 delivered VBN VERB
    187 from IN ADP
    188 my PRP$ PRON
    189 heart NN NOUN
    190 . . PUNCT
    191 A DT DET
    192 new JJ ADJ
    193 chapter NN NOUN
    194 of IN ADP
    195 American JJ ADJ
    196 greatness NN NOUN
    197 is VBZ AUX
    198 now RB ADV
    199 beginning VBG VERB
    200 . . PUNCT
    201 A DT DET
    202 new JJ ADJ
    203 national JJ ADJ
    204 pride NN NOUN
    205 is VBZ AUX
    206 sweeping VBG VERB
    207 across IN ADP
    208 our PRP$ PRON
    209 Nation NN NOUN
    210 . . PUNCT
    211 And CC CCONJ
    212 a DT DET
    213 new JJ ADJ
    214 surge NN NOUN
    215 of IN ADP
    216 optimism NN NOUN
    217 is VBZ AUX
    218 placing VBG VERB
    219 impossible JJ ADJ
    220 dreams NNS NOUN
    221 firmly RB ADV
    222 within IN ADP
    223 our PRP$ PRON
    224 grasp NN NOUN
    225 . . PUNCT
    226

     _SP SPACE
    227 What WP PRON
    228 we PRP PRON
    229 are VBP AUX
    230 witnessing VBG VERB
    231 today NN NOUN
    232 is VBZ AUX
    233 the DT DET
    234 renewal NN NOUN
    235 of IN ADP
    236 the DT DET
    237 American JJ ADJ
    238 spirit NN NOUN
    239 . . PUNCT
    240 Our PRP$ PRON
    241 allies NNS NOUN
    242 will MD AUX
    243 find VB VERB
    244 that IN SCONJ
    245 America NNP PROPN
    246 is VBZ AUX
    247 once RB ADV
    248 again RB ADV
    249 ready JJ ADJ
    250 to TO PART
    251 lead VB VERB
    252 . . PUNCT
    253 All PDT DET
    254 the DT DET
    255 nations NNS NOUN
    256 of IN ADP
    257 the DT DET
    258 world NN NOUN
    259 — : PUNCT
    260 friend NN NOUN
    261 or CC CCONJ
    262 foe NN NOUN
    263 — : PUNCT
    264 will MD AUX
    265 find VB VERB
    266 that IN SCONJ
    267 America NNP PROPN
    268 is VBZ AUX
    269 strong JJ ADJ
    270 , , PUNCT
    271 America NNP PROPN
    272 is VBZ AUX
    273 proud JJ ADJ
    274 , , PUNCT
    275 and CC CCONJ
    276 America NNP PROPN
    277 is VBZ VERB
    278 free JJ ADJ
    279 . . PUNCT
    280

     _SP SPACE
    281 In IN ADP
    282 9 CD NUM
    283 years NNS NOUN
    284 , , PUNCT
    285 the DT DET
    286 United NNP PROPN
    287 States NNP PROPN
    288 will MD AUX
    289 celebrate VB VERB
    290 the DT DET
    291 250th JJ ADJ
    292 anniversary NN NOUN
    293 of IN ADP
    294 our PRP$ PRON
    295 founding NN NOUN
    296 : : PUNCT
    297 250 CD NUM
    298 years NNS NOUN
    299 since IN SCONJ
    300 the DT DET
    301 day NN NOUN
    302 we PRP PRON
    303 declared VBD VERB
    304 our PRP$ PRON
    305 independence NN NOUN
    306 . . PUNCT
    307 It PRP PRON
    308 will MD AUX
    309 be VB VERB
    310 one CD NUM
    311 of IN ADP
    312 the DT DET
    313 great JJ ADJ
    314 milestones NNS NOUN
    315 in IN ADP
    316 the DT DET
    317 history NN NOUN
    318 of IN ADP
    319 the DT DET
    320 world NN NOUN
    321 . . PUNCT
    322 But CC CCONJ
    323 what WP PRON
    324 will MD AUX
    325 America NNP PROPN
    326 look VB VERB
    327 like IN ADP
    328 as IN ADP
    329 we PRP PRON
    330 reach VBP VERB
    331 our PRP$ PRON
    332 250th JJ ADJ
    333 year NN NOUN
    334 ? . PUNCT
    335 What WDT DET
    336 kind NN NOUN
    337 of IN ADP
    338 country NN NOUN
    339 will MD AUX
    340 we PRP PRON
    341 leave VB VERB
    342 for IN ADP
    343 our PRP$ PRON
    344 children NNS NOUN
    345 ? . PUNCT
    346

     _SP SPACE
    347 I PRP PRON
    348 will MD AUX
    349 not RB PART
    350 allow VB VERB
    351 the DT DET
    352 mistakes NNS NOUN
    353 of IN ADP
    354 recent JJ ADJ
    355 decades NNS NOUN
    356 past JJ ADJ
    357 to TO PART
    358 define VB VERB
    359 the DT DET
    360 course NN NOUN
    361 of IN ADP
    362 our PRP$ PRON
    363 future NN NOUN
    364 . . PUNCT
    365 For IN ADP
    366 too RB ADV
    367 long RB ADV
    368 , , PUNCT
    369 we PRP PRON
    370 've VBP AUX
    371 watched VBN VERB
    372 our PRP$ PRON
    373 middle JJ ADJ
    374 class NN NOUN
    375 shrink NN NOUN
    376 as IN ADP
    377 we PRP PRON
    378 've VBP AUX
    379 exported VBN VERB
    380 our PRP$ PRON
    381 jobs NNS NOUN
    382 and CC CCONJ
    383 wealth NN NOUN
    384 to IN ADP
    385 foreign JJ ADJ
    386 countries NNS NOUN
    387 . . PUNCT
    388 We PRP PRON
    389 've VBP AUX
    390 financed VBN VERB
    391 and CC CCONJ
    392 built VBD VERB
    393 one CD NUM
    394 global JJ ADJ
    395 project NN NOUN
    396 after IN ADP
    397 another DT DET
    398 , , PUNCT
    399 but CC CCONJ
    400 ignored VBD VERB
    401 the DT DET
    402 fates NNS NOUN
    403 of IN ADP
    404 our PRP$ PRON
    405 children NNS NOUN
    406 in IN ADP
    407 the DT DET
    408 inner JJ ADJ
    409 cities NNS NOUN
    410 of IN ADP
    411 Chicago NNP PROPN
    412 , , PUNCT
    413 Baltimore NNP PROPN
    414 , , PUNCT
    415 Detroit NNP PROPN
    416 , , PUNCT
    417 and CC CCONJ
    418 so RB ADV
    419 many JJ ADJ
    420 other JJ ADJ
    421 places NNS NOUN
    422 throughout IN ADP
    423 our PRP$ PRON
    424 land NN NOUN
    425 . . PUNCT
    426

     _SP SPACE
    427 We PRP PRON
    428 've VBP AUX
    429 defended VBN VERB
    430 the DT DET
    431 borders NNS NOUN
    432 of IN ADP
    433 other JJ ADJ
    434 nations NNS NOUN
    435 , , PUNCT
    436 while IN SCONJ
    437 leaving VBG VERB
    438 our PRP$ PRON
    439 own JJ ADJ
    440 borders NNS NOUN
    441 wide RB ADV
    442 open JJ ADJ
    443 for IN ADP
    444 anyone NN PRON
    445 to TO PART
    446 cross VB VERB
    447 and CC CCONJ
    448 for IN ADP
    449 drugs NNS NOUN
    450 to TO PART
    451 pour VB VERB
    452 in RP ADP
    453 at IN ADP
    454 a DT DET
    455 now RB ADV
    456 unprecedented JJ ADJ
    457 rate NN NOUN
    458 . . PUNCT
    459 And CC CCONJ
    460 we PRP PRON
    461 've VBP AUX
    462 spent VBN VERB
    463 trillions NNS NOUN
    464 and CC CCONJ
    465 trillions NNS NOUN
    466 of IN ADP
    467 dollars NNS NOUN
    468 overseas RB ADV
    469 , , PUNCT
    470 while IN SCONJ
    471 our PRP$ PRON
    472 infrastructure NN NOUN
    473 at IN ADP
    474 home NN NOUN
    475 has VBZ AUX
    476 so RB ADV
    477 badly RB ADV
    478 crumbled VBN VERB
    479 . . PUNCT
    480

     _SP SPACE
    481 Then RB ADV
    482 , , PUNCT
    483 in IN ADP
    484 2016 CD NUM
    485 , , PUNCT
    486 the DT DET
    487 Earth NNP PROPN
    488 shifted VBD VERB
    489 beneath IN ADP
    490 our PRP$ PRON
    491 feet NNS NOUN
    492 . . PUNCT
    493 The DT DET
    494 rebellion NN NOUN
    495 started VBD VERB
    496 as IN ADP
    497 a DT DET
    498 quiet JJ ADJ
    499 protest NN NOUN
    500 , , PUNCT
    501 spoken VBN VERB
    502 by IN ADP
    503 families NNS NOUN
    504 of IN ADP
    505 all DT DET
    506 colors NNS NOUN
    507 and CC CCONJ
    508 creeds NNS NOUN
    509 , , PUNCT
    510 families NNS NOUN
    511 who WP PRON
    512 just RB ADV
    513 wanted VBD VERB
    514 a DT DET
    515 fair JJ ADJ
    516 shot NN NOUN
    517 for IN ADP
    518 their PRP$ PRON
    519 children NNS NOUN
    520 and CC CCONJ
    521 a DT DET
    522 fair JJ ADJ
    523 hearing NN NOUN
    524 for IN ADP
    525 their PRP$ PRON
    526 concerns NNS NOUN
    527 . . PUNCT
    528

     _SP SPACE
    529 But CC CCONJ
    530 then RB ADV
    531 the DT DET
    532 quiet JJ ADJ
    533 voices NNS NOUN
    534 became VBD VERB
    535 a DT DET
    536 loud JJ ADJ
    537 chorus NN NOUN
    538 , , PUNCT
    539 as IN ADP
    540 thousands NNS NOUN
    541 of IN ADP
    542 citizens NNS NOUN
    543 now RB ADV
    544 spoke VBD VERB
    545 out RP ADP
    546 together RB ADV
    547 , , PUNCT
    548 from IN ADP
    549 cities NNS NOUN
    550 small JJ ADJ
    551 and CC CCONJ
    552 large JJ ADJ
    553 , , PUNCT
    554 all RB ADV
    555 across IN ADP
    556 our PRP$ PRON
    557 country NN NOUN
    558 . . PUNCT
    559 Finally RB ADV
    560 , , PUNCT
    561 the DT DET
    562 chorus NN NOUN
    563 became VBD VERB
    564 an DT DET
    565 earthquake NN NOUN
    566 , , PUNCT
    567 and CC CCONJ
    568 the DT DET
    569 people NNS NOUN
    570 turned VBD VERB
    571 out RP ADP
    572 by IN ADP
    573 the DT DET
    574 tens NNS NOUN
    575 of IN ADP
    576 millions NNS NOUN
    577 , , PUNCT
    578 and CC CCONJ
    579 they PRP PRON
    580 were VBD AUX
    581 all RB ADV
    582 united VBN VERB
    583 by IN ADP
    584 one CD NUM
    585 very RB ADV
    586 simple JJ ADJ
    587 , , PUNCT
    588 but CC CCONJ
    589 crucial JJ ADJ
    590 demand NN NOUN
    591 : : PUNCT
    592 that IN SCONJ
    593 America NNP PROPN
    594 must MD AUX
    595 put VB VERB
    596 its PRP$ PRON
    597 own JJ ADJ
    598 citizens NNS NOUN
    599 first RB ADV
    600 . . PUNCT
    601 Because IN SCONJ
    602 only RB ADV
    603 then RB ADV
    604 can MD AUX
    605 we PRP PRON
    606 truly RB ADV
    607 make VB VERB
    608 America NNP PROPN
    609 great JJ ADJ
    610 again RB ADV
    611 . . PUNCT
    612

     _SP SPACE
    613 Dying VBG VERB
    614 industries NNS NOUN
    615 will MD AUX
    616 come VB VERB
    617 roaring VBG VERB
    618 back RB ADV
    619 to IN ADP
    620 life NN NOUN
    621 . . PUNCT
    622 Heroic JJ ADJ
    623 veterans NNS NOUN
    624 will MD AUX
    625 get VB VERB
    626 the DT DET
    627 care NN NOUN
    628 they PRP PRON
    629 so RB ADV
    630 desperately RB ADV
    631 need VBP VERB
    632 . . PUNCT
    633 Our PRP$ PRON
    634 military NN NOUN
    635 will MD AUX
    636 be VB AUX
    637 given VBN VERB
    638 the DT DET
    639 resources NNS NOUN
    640 its PRP$ PRON
    641 brave JJ ADJ
    642 warriors NNS NOUN
    643 so RB ADV
    644 richly RB ADV
    645 deserve VBP VERB
    646 . . PUNCT
    647 Crumbling VBG VERB
    648 infrastructure NN NOUN
    649 will MD AUX
    650 be VB AUX
    651 replaced VBN VERB
    652 with IN ADP
    653 new JJ ADJ
    654 roads NNS NOUN
    655 , , PUNCT
    656 bridges NNS NOUN
    657 , , PUNCT
    658 tunnels NNS NOUN
    659 , , PUNCT
    660 airports NNS NOUN
    661 , , PUNCT
    662 and CC CCONJ
    663 railways VBZ VERB
    664 gleaming VBG VERB
    665 across IN ADP
    666 our PRP$ PRON
    667 very RB ADV
    668 , , PUNCT
    669 very RB ADV
    670 beautiful JJ ADJ
    671 land NN NOUN
    672 . . PUNCT
    673 Our PRP$ PRON
    674 terrible JJ ADJ
    675 drug NN NOUN
    676 epidemic NN NOUN
    677 will MD AUX
    678 slow VB VERB
    679 down RP ADP
    680 and CC CCONJ
    681 , , PUNCT
    682 ultimately RB ADV
    683 , , PUNCT
    684 stop VB VERB
    685 . . PUNCT
    686 And CC CCONJ
    687 our PRP$ PRON
    688 neglected VBN VERB
    689 inner JJ ADJ
    690 cities NNS NOUN
    691 will MD AUX
    692 see VB VERB
    693 a DT DET
    694 rebirth NN NOUN
    695 of IN ADP
    696 hope NN NOUN
    697 , , PUNCT
    698 safety NN NOUN
    699 , , PUNCT
    700 and CC CCONJ
    701 opportunity NN NOUN
    702 . . PUNCT
    703 Above IN ADP
    704 all DT DET
    705 else RB ADV
    706 , , PUNCT
    707 we PRP PRON
    708 will MD AUX
    709 keep VB VERB
    710 our PRP$ PRON
    711 promises NNS NOUN
    712 to IN ADP
    713 the DT DET
    714 American JJ ADJ
    715 people NNS NOUN
    716 . . PUNCT
    717 [ XX X
    718 Applause XX X
    719 ] XX X
    720 Thank VBP VERB
    721 you PRP PRON
    722 . . PUNCT
    723

     _SP SPACE
    724 It PRP PRON
    725 's VBZ AUX
    726 been VBN VERB
    727 a DT DET
    728 little JJ ADJ
    729 over IN ADP
    730 a DT DET
    731 month NN NOUN
    732 since IN SCONJ
    733 my PRP$ PRON
    734 Inauguration NNP PROPN
    735 , , PUNCT
    736 and CC CCONJ
    737 I PRP PRON
    738 want VBP VERB
    739 to TO PART
    740 take VB VERB
    741 this DT DET
    742 moment NN NOUN
    743 to TO PART
    744 update VB VERB
    745 the DT DET
    746 Nation NN NOUN
    747 on IN ADP
    748 the DT DET
    749 progress NN NOUN
    750 I PRP PRON
    751 've VBP AUX
    752 made VBN VERB
    753 in IN ADP
    754 keeping VBG VERB
    755 those DT DET
    756 promises NNS NOUN
    757 . . PUNCT
    758

     _SP SPACE
    759 Since IN SCONJ
    760 my PRP$ PRON
    761 election NN NOUN
    762 , , PUNCT
    763 Ford NNP PROPN
    764 , , PUNCT
    765 Fiat NNP PROPN
    766 Chrysler NNP PROPN
    767 , , PUNCT
    768 General NNP PROPN
    769 Motors NNPS PROPN
    770 , , PUNCT
    771 Sprint NNP PROPN
    772 , , PUNCT
    773 Softbank NNP PROPN
    774 , , PUNCT
    775 Lockheed NNP PROPN
    776 , , PUNCT
    777 Intel NNP PROPN
    778 , , PUNCT
    779 Walmart NNP PROPN
    780 , , PUNCT
    781 and CC CCONJ
    782 many JJ ADJ
    783 others NNS NOUN
    784 have VBP AUX
    785 announced VBN VERB
    786 that IN SCONJ
    787 they PRP PRON
    788 will MD AUX
    789 invest VB VERB
    790 billions NNS NOUN
    791 and CC CCONJ
    792 billions NNS NOUN
    793 of IN ADP
    794 dollars NNS NOUN
    795 in IN ADP
    796 the DT DET
    797 United NNP PROPN
    798 States NNP PROPN
    799 and CC CCONJ
    800 will MD AUX
    801 create VB VERB
    802 tens NNS NOUN
    803 of IN ADP
    804 thousands NNS NOUN
    805 of IN ADP
    806 new JJ ADJ
    807 American JJ ADJ
    808 jobs NNS NOUN
    809 . . PUNCT
    810

     _SP SPACE
    811 The DT DET
    812 stock NN NOUN
    813 market NN NOUN
    814 has VBZ AUX
    815 gained VBN VERB
    816 almost RB ADV
    817 $ $ SYM
    818 3 CD NUM
    819 trillion CD NUM
    820 in IN ADP
    821 value NN NOUN
    822 since IN SCONJ
    823 the DT DET
    824 election NN NOUN
    825 on IN ADP
    826 November NNP PROPN
    827 8 CD NUM
    828 — : PUNCT
    829 a DT DET
    830 record NN NOUN
    831 . . PUNCT
    832 We PRP PRON
    833 've VBP AUX
    834 saved VBN VERB
    835 taxpayers NNS NOUN
    836 hundreds NNS NOUN
    837 of IN ADP
    838 millions NNS NOUN
    839 of IN ADP
    840 dollars NNS NOUN
    841 by IN ADP
    842 bringing VBG VERB
    843 down RP ADP
    844 the DT DET
    845 price NN NOUN
    846 of IN ADP
    847 fantastic NN NOUN
    848 — : PUNCT
    849 and CC CCONJ
    850 it PRP PRON
    851 is VBZ VERB
    852 a DT DET
    853 fantastic JJ ADJ
    854 — : PUNCT
    855 new JJ ADJ
    856 F-35 CD NUM
    857 jet NN NOUN
    858 fighter NN NOUN
    859 , , PUNCT
    860 and CC CCONJ
    861 we PRP PRON
    862 'll MD AUX
    863 be VB AUX
    864 saving VBG VERB
    865 billions NNS NOUN
    866 more RBR ADV
    867 on IN ADP
    868 contracts NNS NOUN
    869 all RB ADV
    870 across IN ADP
    871 our PRP$ PRON
    872 Government NNP PROPN
    873 . . PUNCT
    874 We PRP PRON
    875 have VBP AUX
    876 placed VBN VERB
    877 a DT DET
    878 hiring VBG VERB
    879 freeze NN NOUN
    880 on IN ADP
    881 nonmilitary JJ ADJ
    882 and CC CCONJ
    883 nonessential JJ ADJ
    884 Federal JJ ADJ
    885 workers NNS NOUN
    886 . . PUNCT
    887

     _SP SPACE
    888 We PRP PRON
    889 have VBP AUX
    890 begun VBN VERB
    891 to TO PART
    892 drain VB VERB
    893 the DT DET
    894 swamp NN NOUN
    895 of IN ADP
    896 government NN NOUN
    897 corruption NN NOUN
    898 by IN ADP
    899 imposing VBG VERB
    900 a DT DET
    901 5 CD NUM
    902 - HYPH PUNCT
    903 year NN NOUN
    904 ban NN NOUN
    905 on IN ADP
    906 lobbying NN NOUN
    907 by IN ADP
    908 executive JJ ADJ
    909 branch NN NOUN
    910 officials NNS NOUN
    911 and CC CCONJ
    912 a DT DET
    913 lifetime NN NOUN
    914 ban—[applause]—thank NN NOUN
    915 you PRP PRON
    916 . . PUNCT
    917 Thank VBP VERB
    918 you PRP PRON
    919 . . PUNCT
    920 And CC CCONJ
    921 a DT DET
    922 lifetime NN NOUN
    923 ban NN NOUN
    924 on IN ADP
    925 becoming VBG VERB
    926 lobbyists NNS NOUN
    927 for IN ADP
    928 a DT DET
    929 foreign JJ ADJ
    930 government NN NOUN
    931 . . PUNCT
    932

     _SP SPACE
    933 We PRP PRON
    934 have VBP AUX
    935 undertaken VBN VERB
    936 a DT DET
    937 historic JJ ADJ
    938 effort NN NOUN
    939 to TO PART
    940 massively RB ADV
    941 reduce VB VERB
    942 job NN NOUN
    943 - HYPH PUNCT
    944 crushing VBG VERB
    945 regulations NNS NOUN
    946 , , PUNCT
    947 creating VBG VERB
    948 a DT DET
    949 deregulation NN NOUN
    950 Task NNP PROPN
    951 Force NNP PROPN
    952 inside RB ADV
    953 of IN ADP
    954 every DT DET
    955 Government NNP PROPN
    956 agency NN NOUN
    957 . . PUNCT
    958 And CC CCONJ
    959 we PRP PRON
    960 're VBP AUX
    961 imposing VBG VERB
    962 a DT DET
    963 new JJ ADJ
    964 rule NN NOUN
    965 which WDT DET
    966 mandates VBZ VERB
    967 that IN SCONJ
    968 for IN ADP
    969 every DT DET
    970 one CD NUM
    971 new JJ ADJ
    972 regulation NN NOUN
    973 , , PUNCT
    974 two CD NUM
    975 old JJ ADJ
    976 regulations NNS NOUN
    977 must MD AUX
    978 be VB AUX
    979 eliminated VBN VERB
    980 . . PUNCT
    981 We PRP PRON
    982 're VBP AUX
    983 going VBG VERB
    984 to TO PART
    985 stop VB VERB
    986 the DT DET
    987 regulations NNS NOUN
    988 that WDT DET
    989 threaten VBP VERB
    990 the DT DET
    991 future NN NOUN
    992 and CC CCONJ
    993 livelihood NN NOUN
    994 of IN ADP
    995 our PRP$ PRON
    996 great JJ ADJ
    997 coal NN NOUN
    998 miners NNS NOUN
    999 . . PUNCT
    1000

     _SP SPACE
    1001 We PRP PRON
    1002 have VBP AUX
    1003 cleared VBN VERB
    1004 the DT DET
    1005 way NN NOUN
    1006 for IN ADP
    1007 the DT DET
    1008 construction NN NOUN
    1009 of IN ADP
    1010 the DT DET
    1011 Keystone NNP PROPN
    1012 and CC CCONJ
    1013 Dakota NNP PROPN
    1014 Access NNP PROPN
    1015 pipelines NNS NOUN
    1016 , , PUNCT
    1017 thereby RB ADV
    1018 creating VBG VERB
    1019 tens NNS NOUN
    1020 of IN ADP
    1021 thousands NNS NOUN
    1022 of IN ADP
    1023 jobs NNS NOUN
    1024 . . PUNCT
    1025 And CC CCONJ
    1026 I PRP PRON
    1027 've VBP AUX
    1028 issued VBN VERB
    1029 a DT DET
    1030 new JJ ADJ
    1031 directive NN NOUN
    1032 that WDT DET
    1033 new JJ ADJ
    1034 American JJ ADJ
    1035 pipelines NNS NOUN
    1036 be VB AUX
    1037 made VBN VERB
    1038 with IN ADP
    1039 American JJ ADJ
    1040 steel NN NOUN
    1041 . . PUNCT
    1042

     _SP SPACE
    1043 We PRP PRON
    1044 have VBP AUX
    1045 withdrawn VBN VERB
    1046 the DT DET
    1047 United NNP PROPN
    1048 States NNP PROPN
    1049 from IN ADP
    1050 the DT DET
    1051 job NN NOUN
    1052 - HYPH PUNCT
    1053 killing VBG VERB
    1054 Trans NNP PROPN
    1055 - NNP PROPN
    1056 Pacific NNP PROPN
    1057 Partnership NNP PROPN
    1058 . . PUNCT
    1059 And CC CCONJ
    1060 with IN ADP
    1061 the DT DET
    1062 help NN NOUN
    1063 of IN ADP
    1064 Prime NNP PROPN
    1065 Minister NNP PROPN
    1066 Justin NNP PROPN
    1067 Trudeau NNP PROPN
    1068 , , PUNCT
    1069 we PRP PRON
    1070 have VBP AUX
    1071 formed VBN VERB
    1072 a DT DET
    1073 council NN NOUN
    1074 with IN ADP
    1075 our PRP$ PRON
    1076 neighbors NNS NOUN
    1077 in IN ADP
    1078 Canada NNP PROPN
    1079 to TO PART
    1080 help VB VERB
    1081 ensure VB VERB
    1082 that IN SCONJ
    1083 women NNS NOUN
    1084 entrepreneurs NNS NOUN
    1085 have VBP VERB
    1086 access NN NOUN
    1087 to IN ADP
    1088 the DT DET
    1089 networks NNS NOUN
    1090 , , PUNCT
    1091 markets NNS NOUN
    1092 , , PUNCT
    1093 and CC CCONJ
    1094 capital NN NOUN
    1095 they PRP PRON
    1096 need VBP VERB
    1097 to TO PART
    1098 start VB VERB
    1099 a DT DET
    1100 business NN NOUN
    1101 and CC CCONJ
    1102 live VB VERB
    1103 out RP ADP
    1104 their PRP$ PRON
    1105 financial JJ ADJ
    1106 dreams NNS NOUN
    1107 . . PUNCT
    1108

     _SP SPACE
    1109 To TO PART
    1110 protect VB VERB
    1111 our PRP$ PRON
    1112 citizens NNS NOUN
    1113 , , PUNCT
    1114 I PRP PRON
    1115 have VBP AUX
    1116 directed VBN VERB
    1117 the DT DET
    1118 Department NNP PROPN
    1119 of IN ADP
    1120 Justice NNP PROPN
    1121 to TO PART
    1122 form VB VERB
    1123 a DT DET
    1124 Task NNP PROPN
    1125 Force NNP PROPN
    1126 on IN ADP
    1127 Reducing VBG VERB
    1128 Violent NNP PROPN
    1129 Crime NNP PROPN
    1130 . . PUNCT
    1131 I PRP PRON
    1132 have VBP AUX
    1133 further RB ADV
    1134 ordered VBN VERB
    1135 the DT DET
    1136 Departments NNPS PROPN
    1137 of IN ADP
    1138 Homeland NNP PROPN
    1139 Security NNP PROPN
    1140 and CC CCONJ
    1141 Justice NNP PROPN
    1142 , , PUNCT
    1143 along IN ADP
    1144 with IN ADP
    1145 the DT DET
    1146 Department NNP PROPN
    1147 of IN ADP
    1148 State NNP PROPN
    1149 and CC CCONJ
    1150 the DT DET
    1151 Director NNP PROPN
    1152 of IN ADP
    1153 National NNP PROPN
    1154 Intelligence NNP PROPN
    1155 , , PUNCT
    1156 to TO PART
    1157 coordinate VB VERB
    1158 an DT DET
    1159 aggressive JJ ADJ
    1160 strategy NN NOUN
    1161 to TO PART
    1162 dismantle VB VERB
    1163 the DT DET
    1164 criminal JJ ADJ
    1165 cartels NNS NOUN
    1166 that WDT DET
    1167 have VBP AUX
    1168 spread VBN VERB
    1169 all RB ADV
    1170 across IN ADP
    1171 our PRP$ PRON
    1172 Nation NN NOUN
    1173 . . PUNCT
    1174 We PRP PRON
    1175 will MD AUX
    1176 stop VB VERB
    1177 the DT DET
    1178 drugs NNS NOUN
    1179 from IN ADP
    1180 pouring VBG VERB
    1181 into IN ADP
    1182 our PRP$ PRON
    1183 country NN NOUN
    1184 and CC CCONJ
    1185 poisoning VBG VERB
    1186 our PRP$ PRON
    1187 youth NN NOUN
    1188 , , PUNCT
    1189 and CC CCONJ
    1190 we PRP PRON
    1191 will MD AUX
    1192 expand VB VERB
    1193 treatment NN NOUN
    1194 for IN ADP
    1195 those DT DET
    1196 who WP PRON
    1197 have VBP AUX
    1198 become VBN VERB
    1199 so RB ADV
    1200 badly RB ADV
    1201 addicted JJ ADJ
    1202 . . PUNCT
    1203

     _SP SPACE
    1204 At IN ADP
    1205 the DT DET
    1206 same JJ ADJ
    1207 time NN NOUN
    1208 , , PUNCT
    1209 my PRP$ PRON
    1210 administration NN NOUN
    1211 has VBZ AUX
    1212 answered VBN VERB
    1213 the DT DET
    1214 pleas NNS NOUN
    1215 of IN ADP
    1216 the DT DET
    1217 American JJ ADJ
    1218 people NNS NOUN
    1219 for IN ADP
    1220 immigration NN NOUN
    1221 enforcement NN NOUN
    1222 and CC CCONJ
    1223 border NN NOUN
    1224 security NN NOUN
    1225 . . PUNCT
    1226 By IN ADP
    1227 finally RB ADV
    1228 enforcing VBG VERB
    1229 our PRP$ PRON
    1230 immigration NN NOUN
    1231 laws NNS NOUN
    1232 , , PUNCT
    1233 we PRP PRON
    1234 will MD AUX
    1235 raise VB VERB
    1236 wages NNS NOUN
    1237 , , PUNCT
    1238 help VB VERB
    1239 the DT DET
    1240 unemployed JJ ADJ
    1241 , , PUNCT
    1242 save VB VERB
    1243 billions NNS NOUN
    1244 and CC CCONJ
    1245 billions NNS NOUN
    1246 of IN ADP
    1247 dollars NNS NOUN
    1248 , , PUNCT
    1249 and CC CCONJ
    1250 make VB VERB
    1251 our PRP$ PRON
    1252 communities NNS NOUN
    1253 safer JJR ADJ
    1254 for IN ADP
    1255 everyone NN PRON
    1256 . . PUNCT
    1257 We PRP PRON
    1258 want VBP VERB
    1259 all DT DET
    1260 Americans NNPS PROPN
    1261 to TO PART
    1262 succeed VB VERB
    1263 , , PUNCT
    1264 but CC CCONJ
    1265 that DT DET
    1266 ca MD AUX
    1267 n't RB PART
    1268 happen VB VERB
    1269 in IN ADP
    1270 an DT DET
    1271 environment NN NOUN
    1272 of IN ADP
    1273 lawless JJ ADJ
    1274 chaos NN NOUN
    1275 . . PUNCT
    1276 We PRP PRON
    1277 must MD AUX
    1278 restore VB VERB
    1279 integrity NN NOUN
    1280 and CC CCONJ
    1281 the DT DET
    1282 rule NN NOUN
    1283 of IN ADP
    1284 law NN NOUN
    1285 at IN ADP
    1286 our PRP$ PRON
    1287 borders NNS NOUN
    1288 . . PUNCT
    1289

     _SP SPACE
    1290 For IN ADP
    1291 that DT DET
    1292 reason NN NOUN
    1293 , , PUNCT
    1294 we PRP PRON
    1295 will MD AUX
    1296 soon RB ADV
    1297 begin VB VERB
    1298 the DT DET
    1299 construction NN NOUN
    1300 of IN ADP
    1301 a DT DET
    1302 great JJ ADJ
    1303 , , PUNCT
    1304 great JJ ADJ
    1305 wall NN NOUN
    1306 along IN ADP
    1307 our PRP$ PRON
    1308 southern JJ ADJ
    1309 border NN NOUN
    1310 . . PUNCT
    1311 As IN ADP
    1312 we PRP PRON
    1313 speak VBP VERB
    1314 tonight NN NOUN
    1315 , , PUNCT
    1316 we PRP PRON
    1317 are VBP AUX
    1318 removing VBG VERB
    1319 gang NN NOUN
    1320 members NNS NOUN
    1321 , , PUNCT
    1322 drug NN NOUN
    1323 dealers NNS NOUN
    1324 , , PUNCT
    1325 and CC CCONJ
    1326 criminals NNS NOUN
    1327 that WDT DET
    1328 threaten VBP VERB
    1329 our PRP$ PRON
    1330 communities NNS NOUN
    1331 and CC CCONJ
    1332 prey NN NOUN
    1333 on IN ADP
    1334 our PRP$ PRON
    1335 very RB ADV
    1336 innocent JJ ADJ
    1337 citizens NNS NOUN
    1338 . . PUNCT
    1339 Bad JJ ADJ
    1340 ones NNS NOUN
    1341 are VBP AUX
    1342 going VBG VERB
    1343 out RP ADP
    1344 as IN ADP
    1345 I PRP PRON
    1346 speak VBP VERB
    1347 , , PUNCT
    1348 and CC CCONJ
    1349 as IN ADP
    1350 I PRP PRON
    1351 've VBP AUX
    1352 promised VBN VERB
    1353 throughout IN ADP
    1354 the DT DET
    1355 campaign NN NOUN
    1356 . . PUNCT
    1357

     _SP SPACE
    1358 To IN ADP
    1359 any DT DET
    1360 in IN ADP
    1361 Congress NNP PROPN
    1362 who WP PRON
    1363 do VBP AUX
    1364 not RB PART
    1365 believe VB VERB
    1366 we PRP PRON
    1367 should MD AUX
    1368 enforce VB VERB
    1369 our PRP$ PRON
    1370 laws NNS NOUN
    1371 , , PUNCT
    1372 I PRP PRON
    1373 would MD AUX
    1374 ask VB VERB
    1375 you PRP PRON
    1376 this DT DET
    1377 one CD NUM
    1378 question NN NOUN
    1379 : : PUNCT
    1380 What WP PRON
    1381 would MD AUX
    1382 you PRP PRON
    1383 say VB VERB
    1384 to IN ADP
    1385 the DT DET
    1386 American JJ ADJ
    1387 family NN NOUN
    1388 that WDT DET
    1389 loses VBZ VERB
    1390 their PRP$ PRON
    1391 jobs NNS NOUN
    1392 , , PUNCT
    1393 their PRP$ PRON
    1394 income NN NOUN
    1395 , , PUNCT
    1396 or CC CCONJ
    1397 their PRP$ PRON
    1398 loved VBN VERB
    1399 one NN NOUN
    1400 because IN SCONJ
    1401 America NNP PROPN
    1402 refused VBD VERB
    1403 to TO PART
    1404 uphold VB VERB
    1405 its PRP$ PRON
    1406 laws NNS NOUN
    1407 and CC CCONJ
    1408 defend VB VERB
    1409 its PRP$ PRON
    1410 borders NNS NOUN
    1411 ? . PUNCT
    1412

     _SP SPACE
    1413 Our PRP$ PRON
    1414 obligation NN NOUN
    1415 is VBZ AUX
    1416 to TO PART
    1417 serve VB VERB
    1418 , , PUNCT
    1419 protect VB VERB
    1420 , , PUNCT
    1421 and CC CCONJ
    1422 defend VB VERB
    1423 the DT DET
    1424 citizens NNS NOUN
    1425 of IN ADP
    1426 the DT DET
    1427 United NNP PROPN
    1428 States NNP PROPN
    1429 . . PUNCT
    1430 We PRP PRON
    1431 are VBP AUX
    1432 also RB ADV
    1433 taking VBG VERB
    1434 strong JJ ADJ
    1435 measures NNS NOUN
    1436 to TO PART
    1437 protect VB VERB
    1438 our PRP$ PRON
    1439 Nation NN NOUN
    1440 from IN ADP
    1441 radical JJ ADJ
    1442 Islamic JJ ADJ
    1443 terrorism NN NOUN
    1444 . . PUNCT
    1445 According VBG VERB
    1446 to IN ADP
    1447 data NNS NOUN
    1448 provided VBN VERB
    1449 by IN ADP
    1450 the DT DET
    1451 Department NNP PROPN
    1452 of IN ADP
    1453 Justice NNP PROPN
    1454 , , PUNCT
    1455 the DT DET
    1456 vast JJ ADJ
    1457 majority NN NOUN
    1458 of IN ADP
    1459 individuals NNS NOUN
    1460 convicted VBN VERB
    1461 of IN ADP
    1462 terrorism NN NOUN
    1463 and CC CCONJ
    1464 terrorism NN NOUN
    1465 - HYPH PUNCT
    1466 related VBN VERB
    1467 offenses NNS NOUN
    1468 since IN SCONJ
    1469 9/11 CD NUM
    1470 came VBD VERB
    1471 here RB ADV
    1472 from IN ADP
    1473 outside IN ADP
    1474 of IN ADP
    1475 our PRP$ PRON
    1476 country NN NOUN
    1477 . . PUNCT
    1478 We PRP PRON
    1479 have VBP AUX
    1480 seen VBN VERB
    1481 the DT DET
    1482 attacks NNS NOUN
    1483 at IN ADP
    1484 home NN NOUN
    1485 , , PUNCT
    1486 from IN ADP
    1487 Boston NNP PROPN
    1488 to IN ADP
    1489 San NNP PROPN
    1490 Bernardino NNP PROPN
    1491 to IN ADP
    1492 the DT DET
    1493 Pentagon NNP PROPN
    1494 , , PUNCT
    1495 and CC CCONJ
    1496 , , PUNCT
    1497 yes UH INTJ
    1498 , , PUNCT
    1499 even RB ADV
    1500 the DT DET
    1501 World NNP PROPN
    1502 Trade NNP PROPN
    1503 Center NNP PROPN
    1504 . . PUNCT
    1505

     _SP SPACE
    1506 We PRP PRON
    1507 have VBP AUX
    1508 seen VBN VERB
    1509 the DT DET
    1510 attacks NNS NOUN
    1511 in IN ADP
    1512 France NNP PROPN
    1513 , , PUNCT
    1514 in IN ADP
    1515 Belgium NNP PROPN
    1516 , , PUNCT
    1517 in IN ADP
    1518 Germany NNP PROPN
    1519 , , PUNCT
    1520 and CC CCONJ
    1521 all RB ADV
    1522 over IN ADP
    1523 the DT DET
    1524 world NN NOUN
    1525 . . PUNCT
    1526 It PRP PRON
    1527 is VBZ AUX
    1528 not RB PART
    1529 compassionate JJ ADJ
    1530 , , PUNCT
    1531 but CC CCONJ
    1532 reckless JJ ADJ
    1533 to TO PART
    1534 allow VB VERB
    1535 uncontrolled JJ ADJ
    1536 entry NN NOUN
    1537 from IN ADP
    1538 places NNS NOUN
    1539 where WRB ADV
    1540 proper JJ ADJ
    1541 vetting NN NOUN
    1542 can MD AUX
    1543 not RB PART
    1544 occur VB VERB
    1545 . . PUNCT
    1546 Those DT DET
    1547 given VBN VERB
    1548 the DT DET
    1549 high JJ ADJ
    1550 honor NN NOUN
    1551 of IN ADP
    1552 admission NN NOUN
    1553 to IN ADP
    1554 the DT DET
    1555 United NNP PROPN
    1556 States NNP PROPN
    1557 should MD AUX
    1558 support VB VERB
    1559 this DT DET
    1560 country NN NOUN
    1561 and CC CCONJ
    1562 love VB VERB
    1563 its PRP$ PRON
    1564 people NNS NOUN
    1565 and CC CCONJ
    1566 its PRP$ PRON
    1567 values NNS NOUN
    1568 . . PUNCT
    1569 We PRP PRON
    1570 can MD AUX
    1571 not RB PART
    1572 allow VB VERB
    1573 a DT DET
    1574 beachhead NN NOUN
    1575 of IN ADP
    1576 terrorism NN NOUN
    1577 to TO PART
    1578 form VB VERB
    1579 inside IN ADP
    1580 America NNP PROPN
    1581 . . PUNCT
    1582 We PRP PRON
    1583 can MD AUX
    1584 not RB PART
    1585 allow VB VERB
    1586 our PRP$ PRON
    1587 Nation NN NOUN
    1588 to TO PART
    1589 become VB VERB
    1590 a DT DET
    1591 sanctuary NN NOUN
    1592 for IN ADP
    1593 extremists NNS NOUN
    1594 . . PUNCT
    1595

     _SP SPACE
    1596 That DT DET
    1597 is VBZ AUX
    1598 why WRB ADV
    1599 my PRP$ PRON
    1600 administration NN NOUN
    1601 has VBZ AUX
    1602 been VBN AUX
    1603 working VBG VERB
    1604 on IN ADP
    1605 improved JJ ADJ
    1606 vetting NN NOUN
    1607 procedures NNS NOUN
    1608 , , PUNCT
    1609 and CC CCONJ
    1610 we PRP PRON
    1611 will MD AUX
    1612 shortly RB ADV
    1613 take VB VERB
    1614 new JJ ADJ
    1615 steps NNS NOUN
    1616 to TO PART
    1617 keep VB VERB
    1618 our PRP$ PRON
    1619 Nation NN NOUN
    1620 safe JJ ADJ
    1621 and CC CCONJ
    1622 to TO PART
    1623 keep VB VERB
    1624 those DT DET
    1625 out RP ADP
    1626 who WP PRON
    1627 will MD AUX
    1628 do VB VERB
    1629 us PRP PRON
    1630 harm VB VERB
    1631 . . PUNCT
    1632

     _SP SPACE
    1633 As IN ADP
    1634 promised VBN VERB
    1635 , , PUNCT
    1636 I PRP PRON
    1637 directed VBD VERB
    1638 the DT DET
    1639 Department NNP PROPN
    1640 of IN ADP
    1641 Defense NNP PROPN
    1642 to TO PART
    1643 develop VB VERB
    1644 a DT DET
    1645 plan NN NOUN
    1646 to TO PART
    1647 demolish VB VERB
    1648 and CC CCONJ
    1649 destroy VB VERB
    1650 ISIS NNP PROPN
    1651 , , PUNCT
    1652 a DT DET
    1653 network NN NOUN
    1654 of IN ADP
    1655 lawless JJ ADJ
    1656 savages NNS NOUN
    1657 that WDT DET
    1658 have VBP AUX
    1659 slaughtered VBN VERB
    1660 Muslims NNPS PROPN
    1661 and CC CCONJ
    1662 Christians NNPS PROPN
    1663 , , PUNCT
    1664 and CC CCONJ
    1665 men NNS NOUN
    1666 and CC CCONJ
    1667 women NNS NOUN
    1668 and CC CCONJ
    1669 children NNS NOUN
    1670 of IN ADP
    1671 all DT DET
    1672 faiths NNS NOUN
    1673 and CC CCONJ
    1674 all DT DET
    1675 beliefs NNS NOUN
    1676 . . PUNCT
    1677 We PRP PRON
    1678 will MD AUX
    1679 work VB VERB
    1680 with IN ADP
    1681 our PRP$ PRON
    1682 allies NNS NOUN
    1683 , , PUNCT
    1684 including VBG VERB
    1685 our PRP$ PRON
    1686 friends NNS NOUN
    1687 and CC CCONJ
    1688 allies NNS NOUN
    1689 in IN ADP
    1690 the DT DET
    1691 Muslim JJ ADJ
    1692 world NN NOUN
    1693 , , PUNCT
    1694 to TO PART
    1695 extinguish VB VERB
    1696 this DT DET
    1697 vile JJ ADJ
    1698 enemy NN NOUN
    1699 from IN ADP
    1700 our PRP$ PRON
    1701 planet NN NOUN
    1702 . . PUNCT
    1703

     _SP SPACE
    1704 I PRP PRON
    1705 have VBP AUX
    1706 also RB ADV
    1707 imposed VBN VERB
    1708 new JJ ADJ
    1709 sanctions NNS NOUN
    1710 on IN ADP
    1711 entities NNS NOUN
    1712 and CC CCONJ
    1713 individuals NNS NOUN
    1714 who WP PRON
    1715 support VBP VERB
    1716 Iran NNP PROPN
    1717 's POS PART
    1718 ballistic JJ ADJ
    1719 missile NN NOUN
    1720 program NN NOUN
    1721 and CC CCONJ
    1722 reaffirmed VBD VERB
    1723 our PRP$ PRON
    1724 unbreakable JJ ADJ
    1725 alliance NN NOUN
    1726 with IN ADP
    1727 the DT DET
    1728 State NNP PROPN
    1729 of IN ADP
    1730 Israel NNP PROPN
    1731 . . PUNCT
    1732

     _SP SPACE
    1733 Finally RB ADV
    1734 , , PUNCT
    1735 I PRP PRON
    1736 have VBP AUX
    1737 kept VBN VERB
    1738 my PRP$ PRON
    1739 promise NN NOUN
    1740 to TO PART
    1741 appoint VB VERB
    1742 a DT DET
    1743 Justice NN NOUN
    1744 to IN ADP
    1745 the DT DET
    1746 United NNP PROPN
    1747 States NNP PROPN
    1748 Supreme NNP PROPN
    1749 Court NNP PROPN
    1750 , , PUNCT
    1751 from IN ADP
    1752 my PRP$ PRON
    1753 list NN NOUN
    1754 of IN ADP
    1755 20 CD NUM
    1756 judges NNS NOUN
    1757 , , PUNCT
    1758 who WP PRON
    1759 will MD AUX
    1760 defend VB VERB
    1761 our PRP$ PRON
    1762 Constitution NNP PROPN
    1763 . . PUNCT
    1764

     _SP SPACE
    1765 I PRP PRON
    1766 am VBP AUX
    1767 greatly RB ADV
    1768 honored VBN VERB
    1769 to TO PART
    1770 have VB VERB
    1771 Maureen NNP PROPN
    1772 Scalia NNP PROPN
    1773 with IN ADP
    1774 us PRP PRON
    1775 in IN ADP
    1776 the DT DET
    1777 gallery NN NOUN
    1778 tonight NN NOUN
    1779 . . PUNCT
    1780 Thank VBP VERB
    1781 you PRP PRON
    1782 , , PUNCT
    1783 Maureen NNP PROPN
    1784 . . PUNCT
    1785 Her PRP$ PRON
    1786 late JJ ADJ
    1787 , , PUNCT
    1788 great JJ ADJ
    1789 husband NN NOUN
    1790 , , PUNCT
    1791 Antonin NNP PROPN
    1792 Scalia NNP PROPN
    1793 , , PUNCT
    1794 will MD AUX
    1795 forever RB ADV
    1796 be VB VERB
    1797 a DT DET
    1798 symbol NN NOUN
    1799 of IN ADP
    1800 American JJ ADJ
    1801 justice NN NOUN
    1802 . . PUNCT
    1803 To TO PART
    1804 fill VB VERB
    1805 his PRP$ PRON
    1806 seat NN NOUN
    1807 , , PUNCT
    1808 we PRP PRON
    1809 have VBP AUX
    1810 chosen VBN VERB
    1811 Judge NNP PROPN
    1812 Neil NNP PROPN
    1813 Gorsuch NNP PROPN
    1814 , , PUNCT
    1815 a DT DET
    1816 man NN NOUN
    1817 of IN ADP
    1818 incredible JJ ADJ
    1819 skill NN NOUN
    1820 and CC CCONJ
    1821 deep JJ ADJ
    1822 devotion NN NOUN
    1823 to IN ADP
    1824 the DT DET
    1825 law NN NOUN
    1826 . . PUNCT
    1827 He PRP PRON
    1828 was VBD AUX
    1829 confirmed VBN VERB
    1830 unanimously RB ADV
    1831 by IN ADP
    1832 the DT DET
    1833 Court NNP PROPN
    1834 of IN ADP
    1835 Appeals NNPS PROPN
    1836 , , PUNCT
    1837 and CC CCONJ
    1838 I PRP PRON
    1839 am VBP AUX
    1840 asking VBG VERB
    1841 the DT DET
    1842 Senate NNP PROPN
    1843 to TO PART
    1844 swiftly RB ADV
    1845 approve VB VERB
    1846 his PRP$ PRON
    1847 nomination NN NOUN
    1848 . . PUNCT
    1849

     _SP SPACE
    1850 Tonight NN NOUN
    1851 , , PUNCT
    1852 as IN ADP
    1853 I PRP PRON
    1854 outline VBP VERB
    1855 the DT DET
    1856 next JJ ADJ
    1857 steps NNS NOUN
    1858 we PRP PRON
    1859 must MD AUX
    1860 take VB VERB
    1861 as IN ADP
    1862 a DT DET
    1863 country NN NOUN
    1864 , , PUNCT
    1865 we PRP PRON
    1866 must MD AUX
    1867 honestly RB ADV
    1868 acknowledge VB VERB
    1869 the DT DET
    1870 circumstances NNS NOUN
    1871 we PRP PRON
    1872 inherited VBD VERB
    1873 . . PUNCT
    1874 Ninety CD NUM
    1875 - HYPH PUNCT
    1876 four CD NUM
    1877 million CD NUM
    1878 Americans NNPS PROPN
    1879 are VBP AUX
    1880 out IN SCONJ
    1881 of IN ADP
    1882 the DT DET
    1883 labor NN NOUN
    1884 force NN NOUN
    1885 . . PUNCT
    1886 Over IN ADP
    1887 43 CD NUM
    1888 million CD NUM
    1889 people NNS NOUN
    1890 are VBP AUX
    1891 now RB ADV
    1892 living VBG VERB
    1893 in IN ADP
    1894 poverty NN NOUN
    1895 , , PUNCT
    1896 and CC CCONJ
    1897 over IN ADP
    1898 43 CD NUM
    1899 million CD NUM
    1900 Americans NNPS PROPN
    1901 are VBP VERB
    1902 on IN ADP
    1903 food NN NOUN
    1904 stamps NNS NOUN
    1905 . . PUNCT
    1906 More JJR ADJ
    1907 than IN SCONJ
    1908 1 CD NUM
    1909 in IN ADP
    1910 5 CD NUM
    1911 people NNS NOUN
    1912 in IN ADP
    1913 their PRP$ PRON
    1914 prime JJ ADJ
    1915 working NN NOUN
    1916 years NNS NOUN
    1917 are VBP AUX
    1918 not RB PART
    1919 working VBG VERB
    1920 . . PUNCT
    1921 We PRP PRON
    1922 have VBP VERB
    1923 the DT DET
    1924 worst JJS ADJ
    1925 financial JJ ADJ
    1926 recovery NN NOUN
    1927 in IN ADP
    1928 65 CD NUM
    1929 years NNS NOUN
    1930 . . PUNCT
    1931 In IN ADP
    1932 the DT DET
    1933 last JJ ADJ
    1934 8 CD NUM
    1935 years NNS NOUN
    1936 , , PUNCT
    1937 the DT DET
    1938 past JJ ADJ
    1939 administration NN NOUN
    1940 has VBZ AUX
    1941 put VBN VERB
    1942 on RP ADP
    1943 more JJR ADJ
    1944 new JJ ADJ
    1945 debt NN NOUN
    1946 than IN SCONJ
    1947 nearly RB ADV
    1948 all DT DET
    1949 of IN ADP
    1950 the DT DET
    1951 other JJ ADJ
    1952 Presidents NNS NOUN
    1953 combined VBN VERB
    1954 . . PUNCT
    1955

     _SP SPACE
    1956 We PRP PRON
    1957 've VBP AUX
    1958 lost VBN VERB
    1959 more JJR ADJ
    1960 than IN SCONJ
    1961 one CD NUM
    1962 - HYPH PUNCT
    1963 fourth NN NOUN
    1964 of IN ADP
    1965 our PRP$ PRON
    1966 manufacturing NN NOUN
    1967 jobs NNS NOUN
    1968 since IN SCONJ
    1969 NAFTA NNP PROPN
    1970 was VBD AUX
    1971 approved VBN VERB
    1972 , , PUNCT
    1973 and CC CCONJ
    1974 we PRP PRON
    1975 've VBP AUX
    1976 lost VBN VERB
    1977 60,000 CD NUM
    1978 factories NNS NOUN
    1979 since IN SCONJ
    1980 China NNP PROPN
    1981 joined VBD VERB
    1982 the DT DET
    1983 World NNP PROPN
    1984 Trade NNP PROPN
    1985 Organization NNP PROPN
    1986 in IN ADP
    1987 2001 CD NUM
    1988 . . PUNCT
    1989 Our PRP$ PRON
    1990 trade NN NOUN
    1991 deficit NN NOUN
    1992 in IN ADP
    1993 goods NNS NOUN
    1994 with IN ADP
    1995 the DT DET
    1996 world NN NOUN
    1997 last JJ ADJ
    1998 year NN NOUN
    1999 was VBD AUX
    2000 nearly RB ADV
    2001 $ $ SYM
    2002 800 CD NUM
    2003 billion CD NUM
    2004 dollars NNS NOUN
    2005 . . PUNCT
    2006 And CC CCONJ
    2007 overseas RB ADV
    2008 we PRP PRON
    2009 have VBP AUX
    2010 inherited VBN VERB
    2011 a DT DET
    2012 series NN NOUN
    2013 of IN ADP
    2014 tragic JJ ADJ
    2015 foreign JJ ADJ
    2016 policy NN NOUN
    2017 disasters NNS NOUN
    2018 . . PUNCT
    2019 Solving VBG VERB
    2020 these DT DET
    2021 and CC CCONJ
    2022 so RB ADV
    2023 many JJ ADJ
    2024 other JJ ADJ
    2025 pressing VBG VERB
    2026 problems NNS NOUN
    2027 will MD AUX
    2028 require VB VERB
    2029 us PRP PRON
    2030 to TO PART
    2031 work VB VERB
    2032 past IN ADP
    2033 the DT DET
    2034 differences NNS NOUN
    2035 of IN ADP
    2036 party NN NOUN
    2037 . . PUNCT
    2038 It PRP PRON
    2039 will MD AUX
    2040 require VB VERB
    2041 us PRP PRON
    2042 to TO PART
    2043 tap VB VERB
    2044 into IN ADP
    2045 the DT DET
    2046 American JJ ADJ
    2047 spirit NN NOUN
    2048 that WDT DET
    2049 has VBZ AUX
    2050 overcome VBN VERB
    2051 every DT DET
    2052 challenge NN NOUN
    2053 throughout IN ADP
    2054 our PRP$ PRON
    2055 long JJ ADJ
    2056 and CC CCONJ
    2057 storied VBD VERB
    2058 history NN NOUN
    2059 . . PUNCT
    2060 But CC CCONJ
    2061 to TO PART
    2062 accomplish VB VERB
    2063 our PRP$ PRON
    2064 goals NNS NOUN
    2065 at IN ADP
    2066 home NN NOUN
    2067 and CC CCONJ
    2068 abroad RB ADV
    2069 , , PUNCT
    2070 we PRP PRON
    2071 must MD AUX
    2072 restart VB VERB
    2073 the DT DET
    2074 engine NN NOUN
    2075 of IN ADP
    2076 the DT DET
    2077 American JJ ADJ
    2078 economy NN NOUN
    2079 , , PUNCT
    2080 making VBG VERB
    2081 it PRP PRON
    2082 easier JJR ADJ
    2083 for IN ADP
    2084 companies NNS NOUN
    2085 to TO PART
    2086 do VB VERB
    2087 business NN NOUN
    2088 in IN ADP
    2089 the DT DET
    2090 United NNP PROPN
    2091 States NNP PROPN
    2092 , , PUNCT
    2093 and CC CCONJ
    2094 much JJ ADJ
    2095 , , PUNCT
    2096 much RB ADV
    2097 harder RBR ADV
    2098 for IN ADP
    2099 companies NNS NOUN
    2100 to TO PART
    2101 leave VB VERB
    2102 our PRP$ PRON
    2103 country NN NOUN
    2104 . . PUNCT
    2105

     _SP SPACE
    2106 Right RB ADV
    2107 now RB ADV
    2108 American JJ ADJ
    2109 companies NNS NOUN
    2110 are VBP AUX
    2111 taxed VBN VERB
    2112 at IN ADP
    2113 one CD NUM
    2114 of IN ADP
    2115 the DT DET
    2116 highest JJS ADJ
    2117 rates NNS NOUN
    2118 anywhere RB ADV
    2119 in IN ADP
    2120 the DT DET
    2121 world NN NOUN
    2122 . . PUNCT
    2123 My PRP$ PRON
    2124 economic JJ ADJ
    2125 team NN NOUN
    2126 is VBZ AUX
    2127 developing VBG VERB
    2128 historic JJ ADJ
    2129 tax NN NOUN
    2130 reform NN NOUN
    2131 that WDT DET
    2132 will MD AUX
    2133 reduce VB VERB
    2134 the DT DET
    2135 tax NN NOUN
    2136 rate NN NOUN
    2137 on IN ADP
    2138 our PRP$ PRON
    2139 companies NNS NOUN
    2140 so IN SCONJ
    2141 they PRP PRON
    2142 can MD AUX
    2143 compete VB VERB
    2144 and CC CCONJ
    2145 thrive VB VERB
    2146 anywhere RB ADV
    2147 and CC CCONJ
    2148 with IN ADP
    2149 anyone NN PRON
    2150 . . PUNCT
    2151 It PRP PRON
    2152 will MD AUX
    2153 be VB VERB
    2154 a DT DET
    2155 big JJ ADJ
    2156 , , PUNCT
    2157 big JJ ADJ
    2158 cut NN NOUN
    2159 . . PUNCT
    2160

     _SP SPACE
    2161 At IN ADP
    2162 the DT DET
    2163 same JJ ADJ
    2164 time NN NOUN
    2165 , , PUNCT
    2166 we PRP PRON
    2167 will MD AUX
    2168 provide VB VERB
    2169 massive JJ ADJ
    2170 tax NN NOUN
    2171 relief NN NOUN
    2172 for IN ADP
    2173 the DT DET
    2174 middle JJ ADJ
    2175 class NN NOUN
    2176 . . PUNCT
    2177 We PRP PRON
    2178 must MD AUX
    2179 create VB VERB
    2180 a DT DET
    2181 level JJ ADJ
    2182 playing NN NOUN
    2183 field NN NOUN
    2184 for IN ADP
    2185 American JJ ADJ
    2186 companies NNS NOUN
    2187 and CC CCONJ
    2188 our PRP$ PRON
    2189 workers NNS NOUN
    2190 — : PUNCT
    2191 have VBP VERB
    2192 to TO PART
    2193 do VB VERB
    2194 it PRP PRON
    2195 . . PUNCT
    2196 Currently RB ADV
    2197 , , PUNCT
    2198 when WRB ADV
    2199 we PRP PRON
    2200 ship VBP VERB
    2201 products NNS NOUN
    2202 out IN SCONJ
    2203 of IN ADP
    2204 America NNP PROPN
    2205 , , PUNCT
    2206 many JJ ADJ
    2207 other JJ ADJ
    2208 countries NNS NOUN
    2209 make VBP VERB
    2210 us PRP PRON
    2211 pay VB VERB
    2212 very RB ADV
    2213 high JJ ADJ
    2214 tariffs NNS NOUN
    2215 and CC CCONJ
    2216 taxes NNS NOUN
    2217 . . PUNCT
    2218 But CC CCONJ
    2219 when WRB ADV
    2220 foreign JJ ADJ
    2221 companies NNS NOUN
    2222 ship VBP VERB
    2223 their PRP$ PRON
    2224 products NNS NOUN
    2225 into IN ADP
    2226 America NNP PROPN
    2227 , , PUNCT
    2228 we PRP PRON
    2229 charge VBP VERB
    2230 them PRP PRON
    2231 nothing NN PRON
    2232 , , PUNCT
    2233 or CC CCONJ
    2234 almost RB ADV
    2235 nothing NN PRON
    2236 . . PUNCT
    2237

     _SP SPACE
    2238 I PRP PRON
    2239 just RB ADV
    2240 met VBD VERB
    2241 with IN ADP
    2242 officials NNS NOUN
    2243 and CC CCONJ
    2244 workers NNS NOUN
    2245 from IN ADP
    2246 a DT DET
    2247 great JJ ADJ
    2248 American JJ ADJ
    2249 company NN NOUN
    2250 , , PUNCT
    2251 Harley NNP PROPN
    2252 - HYPH PUNCT
    2253 Davidson NNP PROPN
    2254 . . PUNCT
    2255 In IN ADP
    2256 fact NN NOUN
    2257 , , PUNCT
    2258 they PRP PRON
    2259 proudly RB ADV
    2260 displayed VBD VERB
    2261 five CD NUM
    2262 of IN ADP
    2263 their PRP$ PRON
    2264 magnificent JJ ADJ
    2265 motorcycles NNS NOUN
    2266 , , PUNCT
    2267 made VBN VERB
    2268 in IN ADP
    2269 the DT DET
    2270 U.S.A. NNP PROPN
    2271 , , PUNCT
    2272 on IN ADP
    2273 the DT DET
    2274 front JJ ADJ
    2275 lawn NN NOUN
    2276 of IN ADP
    2277 the DT DET
    2278 White NNP PROPN
    2279 House NNP PROPN
    2280 . . PUNCT
    2281 [ XX X
    2282 Laughter XX X
    2283 ] XX X
    2284 And CC CCONJ
    2285 they PRP PRON
    2286 wanted VBD VERB
    2287 me PRP PRON
    2288 to TO PART
    2289 ride VB VERB
    2290 one CD NUM
    2291 , , PUNCT
    2292 and CC CCONJ
    2293 I PRP PRON
    2294 said VBD VERB
    2295 , , PUNCT
    2296 " `` PUNCT
    2297 No UH INTJ
    2298 , , PUNCT
    2299 thank VBP VERB
    2300 you PRP PRON
    2301 . . PUNCT
    2302 " '' PUNCT
    2303 [ XX X
    2304 Laughter NN NOUN
    2305 ] -RRB- PUNCT
    2306

     _SP SPACE
    2307 At IN ADP
    2308 our PRP$ PRON
    2309 meeting NN NOUN
    2310 , , PUNCT
    2311 I PRP PRON
    2312 asked VBD VERB
    2313 them PRP PRON
    2314 , , PUNCT
    2315 how WRB ADV
    2316 are VBP AUX
    2317 you PRP PRON
    2318 doing VBG VERB
    2319 , , PUNCT
    2320 how WRB ADV
    2321 is VBZ VERB
    2322 business NN NOUN
    2323 ? . PUNCT
    2324 They PRP PRON
    2325 said VBD VERB
    2326 that IN SCONJ
    2327 it PRP PRON
    2328 's VBZ AUX
    2329 good JJ ADJ
    2330 . . PUNCT
    2331 I PRP PRON
    2332 asked VBD VERB
    2333 them PRP PRON
    2334 further RBR ADV
    2335 , , PUNCT
    2336 how WRB ADV
    2337 are VBP AUX
    2338 you PRP PRON
    2339 doing VBG VERB
    2340 with IN ADP
    2341 other JJ ADJ
    2342 countries NNS NOUN
    2343 , , PUNCT
    2344 mainly RB ADV
    2345 international JJ ADJ
    2346 sales NNS NOUN
    2347 ? . PUNCT
    2348 They PRP PRON
    2349 told VBD VERB
    2350 me PRP PRON
    2351 — : PUNCT
    2352 without IN ADP
    2353 even RB ADV
    2354 complaining VBG VERB
    2355 , , PUNCT
    2356 because IN SCONJ
    2357 they PRP PRON
    2358 have VBP AUX
    2359 been VBN AUX
    2360 so RB ADV
    2361 mistreated VBN VERB
    2362 for IN ADP
    2363 so RB ADV
    2364 long JJ ADJ
    2365 that IN SCONJ
    2366 they PRP PRON
    2367 've VBP AUX
    2368 become VBN VERB
    2369 used JJ ADJ
    2370 to IN ADP
    2371 it PRP PRON
    2372 — : PUNCT
    2373 that IN SCONJ
    2374 it PRP PRON
    2375 's VBZ AUX
    2376 very RB ADV
    2377 hard JJ ADJ
    2378 to TO PART
    2379 do VB VERB
    2380 business NN NOUN
    2381 with IN ADP
    2382 other JJ ADJ
    2383 countries NNS NOUN
    2384 because IN SCONJ
    2385 they PRP PRON
    2386 tax VBP VERB
    2387 our PRP$ PRON
    2388 goods NNS NOUN
    2389 at IN ADP
    2390 such PDT DET
    2391 a DT DET
    2392 high JJ ADJ
    2393 rate NN NOUN
    2394 . . PUNCT
    2395 They PRP PRON
    2396 said VBD VERB
    2397 that IN SCONJ
    2398 in IN ADP
    2399 the DT DET
    2400 case NN NOUN
    2401 of IN ADP
    2402 another DT DET
    2403 country NN NOUN
    2404 , , PUNCT
    2405 they PRP PRON
    2406 taxed VBD VERB
    2407 their PRP$ PRON
    2408 motorcycles NNS NOUN
    2409 at IN ADP
    2410 100 CD NUM
    2411 percent NN NOUN
    2412 . . PUNCT
    2413 They PRP PRON
    2414 were VBD AUX
    2415 n't RB PART
    2416 even RB ADV
    2417 asking VBG VERB
    2418 for IN ADP
    2419 a DT DET
    2420 change NN NOUN
    2421 . . PUNCT
    2422 But CC CCONJ
    2423 I PRP PRON
    2424 am VBP AUX
    2425 . . PUNCT
    2426

     _SP SPACE
    2427 I PRP PRON
    2428 believe VBP VERB
    2429 strongly RB ADV
    2430 in IN ADP
    2431 free JJ ADJ
    2432 trade NN NOUN
    2433 , , PUNCT
    2434 but CC CCONJ
    2435 it PRP PRON
    2436 also RB ADV
    2437 has VBZ VERB
    2438 to TO PART
    2439 be VB VERB
    2440 fair JJ ADJ
    2441 trade NN NOUN
    2442 . . PUNCT
    2443 It PRP PRON
    2444 's VBZ AUX
    2445 been VBN VERB
    2446 a DT DET
    2447 long JJ ADJ
    2448 time NN NOUN
    2449 since IN SCONJ
    2450 we PRP PRON
    2451 had VBD VERB
    2452 fair JJ ADJ
    2453 trade NN NOUN
    2454 . . PUNCT
    2455 The DT DET
    2456 first JJ ADJ
    2457 Republican JJ ADJ
    2458 President NNP PROPN
    2459 , , PUNCT
    2460 Abraham NNP PROPN
    2461 Lincoln NNP PROPN
    2462 , , PUNCT
    2463 warned VBD VERB
    2464 that IN SCONJ
    2465 the DT DET
    2466 " `` PUNCT
    2467 abandonment NN NOUN
    2468 of IN ADP
    2469 the DT DET
    2470 protective JJ ADJ
    2471 policy NN NOUN
    2472 by IN ADP
    2473 the DT DET
    2474 American NNP PROPN
    2475 Government NNP PROPN
    2476 will MD AUX
    2477 produce VB VERB
    2478 want VB VERB
    2479 and CC CCONJ
    2480 ruin VB VERB
    2481 among IN ADP
    2482 our PRP$ PRON
    2483 people NNS NOUN
    2484 . . PUNCT
    2485 " '' PUNCT
    2486 Lincoln NNP PROPN
    2487 was VBD AUX
    2488 right JJ ADJ
    2489 , , PUNCT
    2490 and CC CCONJ
    2491 it PRP PRON
    2492 's VBZ VERB
    2493 time NN NOUN
    2494 we PRP PRON
    2495 heeded VBD VERB
    2496 his PRP$ PRON
    2497 advice NN NOUN
    2498 and CC CCONJ
    2499 his PRP$ PRON
    2500 words NNS NOUN
    2501 . . PUNCT
    2502 I PRP PRON
    2503 am VBP AUX
    2504 not RB PART
    2505 going VBG VERB
    2506 to TO PART
    2507 let VB VERB
    2508 America NNP PROPN
    2509 and CC CCONJ
    2510 its PRP$ PRON
    2511 great JJ ADJ
    2512 companies NNS NOUN
    2513 and CC CCONJ
    2514 workers NNS NOUN
    2515 be VB AUX
    2516 taken VBN VERB
    2517 advantage NN NOUN
    2518 of IN ADP
    2519 us PRP PRON
    2520 any RB ADV
    2521 longer RBR ADV
    2522 . . PUNCT
    2523 They PRP PRON
    2524 have VBP AUX
    2525 taken VBN VERB
    2526 advantage NN NOUN
    2527 of IN ADP
    2528 our PRP$ PRON
    2529 country NN NOUN
    2530 . . PUNCT
    2531 No RB ADV
    2532 longer RBR ADV
    2533 . . PUNCT
    2534

     _SP SPACE
    2535 I PRP PRON
    2536 am VBP AUX
    2537 going VBG VERB
    2538 to TO PART
    2539 bring VB VERB
    2540 back RB ADV
    2541 millions NNS NOUN
    2542 of IN ADP
    2543 jobs NNS NOUN
    2544 . . PUNCT
    2545 Protecting VBG VERB
    2546 our PRP$ PRON
    2547 workers NNS NOUN
    2548 also RB ADV
    2549 means VBZ VERB
    2550 reforming VBG VERB
    2551 our PRP$ PRON
    2552 system NN NOUN
    2553 of IN ADP
    2554 legal JJ ADJ
    2555 immigration NN NOUN
    2556 . . PUNCT
    2557 The DT DET
    2558 current JJ ADJ
    2559 , , PUNCT
    2560 outdated JJ ADJ
    2561 system NN NOUN
    2562 depresses VBZ VERB
    2563 wages NNS NOUN
    2564 for IN ADP
    2565 our PRP$ PRON
    2566 poorest JJS ADJ
    2567 workers NNS NOUN
    2568 and CC CCONJ
    2569 puts VBZ VERB
    2570 great JJ ADJ
    2571 pressure NN NOUN
    2572 on IN ADP
    2573 taxpayers NNS NOUN
    2574 . . PUNCT
    2575 Nations NNS NOUN
    2576 around IN ADP
    2577 the DT DET
    2578 world NN NOUN
    2579 like IN ADP
    2580 Canada NNP PROPN
    2581 , , PUNCT
    2582 Australia NNP PROPN
    2583 , , PUNCT
    2584 and CC CCONJ
    2585 many JJ ADJ
    2586 others NNS NOUN
    2587 , , PUNCT
    2588 have VBP VERB
    2589 a DT DET
    2590 merit NN NOUN
    2591 - HYPH PUNCT
    2592 based VBN VERB
    2593 immigration NN NOUN
    2594 system NN NOUN
    2595 . . PUNCT
    2596 It PRP PRON
    2597 's VBZ AUX
    2598 a DT DET
    2599 basic JJ ADJ
    2600 principle NN NOUN
    2601 that IN SCONJ
    2602 those DT DET
    2603 seeking VBG VERB
    2604 to TO PART
    2605 enter VB VERB
    2606 a DT DET
    2607 country NN NOUN
    2608 ought MD AUX
    2609 to TO PART
    2610 be VB VERB
    2611 able JJ ADJ
    2612 to TO PART
    2613 support VB VERB
    2614 themselves PRP PRON
    2615 financially RB ADV
    2616 . . PUNCT
    2617 Yet CC CCONJ
    2618 , , PUNCT
    2619 in IN ADP
    2620 America NNP PROPN
    2621 , , PUNCT
    2622 we PRP PRON
    2623 do VBP AUX
    2624 not RB PART
    2625 enforce VB VERB
    2626 this DT DET
    2627 rule NN NOUN
    2628 , , PUNCT
    2629 straining VBG VERB
    2630 the DT DET
    2631 very RB ADV
    2632 public JJ ADJ
    2633 resources NNS NOUN
    2634 that WDT DET
    2635 our PRP$ PRON
    2636 poorest JJS ADJ
    2637 citizens NNS NOUN
    2638 rely VBP VERB
    2639 upon IN SCONJ
    2640 . . PUNCT
    2641 According VBG VERB
    2642 to IN ADP
    2643 the DT DET
    2644 National NNP PROPN
    2645 Academy NNP PROPN
    2646 of IN ADP
    2647 Sciences NNPS PROPN
    2648 , , PUNCT
    2649 our PRP$ PRON
    2650 current JJ ADJ
    2651 immigration NN NOUN
    2652 system NN NOUN
    2653 costs VBZ VERB
    2654 American JJ ADJ
    2655 taxpayers NNS NOUN
    2656 many JJ ADJ
    2657 billions NNS NOUN
    2658 of IN ADP
    2659 dollars NNS NOUN
    2660 a DT DET
    2661 year NN NOUN
    2662 . . PUNCT
    2663

     _SP SPACE
    2664 Switching VBG VERB
    2665 away RB ADV
    2666 from IN ADP
    2667 this DT DET
    2668 current JJ ADJ
    2669 system NN NOUN
    2670 of IN ADP
    2671 lower JJR ADJ
    2672 skilled JJ ADJ
    2673 immigration NN NOUN
    2674 , , PUNCT
    2675 and CC CCONJ
    2676 instead RB ADV
    2677 adopting VBG VERB
    2678 a DT DET
    2679 merit NN NOUN
    2680 - HYPH PUNCT
    2681 based VBN VERB
    2682 system NN NOUN
    2683 , , PUNCT
    2684 we PRP PRON
    2685 will MD AUX
    2686 have VB VERB
    2687 so RB ADV
    2688 many JJ ADJ
    2689 more JJR ADJ
    2690 benefits NNS NOUN
    2691 . . PUNCT
    2692 It PRP PRON
    2693 will MD AUX
    2694 save VB VERB
    2695 countless JJ ADJ
    2696 dollars NNS NOUN
    2697 , , PUNCT
    2698 raise VB VERB
    2699 workers NNS NOUN
    2700 ' POS PART
    2701 wages NNS NOUN
    2702 , , PUNCT
    2703 and CC CCONJ
    2704 help VB VERB
    2705 struggling VBG VERB
    2706 families NNS NOUN
    2707 — : PUNCT
    2708 including VBG VERB
    2709 immigrant JJ ADJ
    2710 families NNS NOUN
    2711 — : PUNCT
    2712 enter VB VERB
    2713 the DT DET
    2714 middle JJ ADJ
    2715 class NN NOUN
    2716 . . PUNCT
    2717 And CC CCONJ
    2718 they PRP PRON
    2719 will MD AUX
    2720 do VB VERB
    2721 it PRP PRON
    2722 quickly RB ADV
    2723 , , PUNCT
    2724 and CC CCONJ
    2725 they PRP PRON
    2726 will MD AUX
    2727 be VB VERB
    2728 very RB ADV
    2729 , , PUNCT
    2730 very RB ADV
    2731 happy JJ ADJ
    2732 , , PUNCT
    2733 indeed RB ADV
    2734 . . PUNCT
    2735

     _SP SPACE
    2736 I PRP PRON
    2737 believe VBP VERB
    2738 that IN SCONJ
    2739 real JJ ADJ
    2740 and CC CCONJ
    2741 positive JJ ADJ
    2742 immigration NN NOUN
    2743 reform NN NOUN
    2744 is VBZ AUX
    2745 possible JJ ADJ
    2746 , , PUNCT
    2747 as RB ADV
    2748 long RB ADV
    2749 as IN ADP
    2750 we PRP PRON
    2751 focus VBP VERB
    2752 on IN ADP
    2753 the DT DET
    2754 following VBG VERB
    2755 goals NNS NOUN
    2756 : : PUNCT
    2757 to TO PART
    2758 improve VB VERB
    2759 jobs NNS NOUN
    2760 and CC CCONJ
    2761 wages NNS NOUN
    2762 for IN ADP
    2763 Americans NNPS PROPN
    2764 , , PUNCT
    2765 to TO PART
    2766 strengthen VB VERB
    2767 our PRP$ PRON
    2768 Nation NN NOUN
    2769 's POS PART
    2770 security NN NOUN
    2771 , , PUNCT
    2772 and CC CCONJ
    2773 to TO PART
    2774 restore VB VERB
    2775 respect NN NOUN
    2776 for IN ADP
    2777 our PRP$ PRON
    2778 laws NNS NOUN
    2779 . . PUNCT
    2780 If IN SCONJ
    2781 we PRP PRON
    2782 are VBP AUX
    2783 guided VBN VERB
    2784 by IN ADP
    2785 the DT DET
    2786 wellbeing NN NOUN
    2787 of IN ADP
    2788 American JJ ADJ
    2789 citizens NNS NOUN
    2790 , , PUNCT
    2791 then RB ADV
    2792 I PRP PRON
    2793 believe VBP VERB
    2794 Republicans NNPS PROPN
    2795 and CC CCONJ
    2796 Democrats NNPS PROPN
    2797 can MD AUX
    2798 work VB VERB
    2799 together RB ADV
    2800 to TO PART
    2801 achieve VB VERB
    2802 an DT DET
    2803 outcome NN NOUN
    2804 that WDT DET
    2805 has VBZ AUX
    2806 eluded VBN VERB
    2807 our PRP$ PRON
    2808 country NN NOUN
    2809 for IN ADP
    2810 decades NNS NOUN
    2811 . . PUNCT
    2812

     _SP SPACE
    2813 Another DT DET
    2814 Republican JJ ADJ
    2815 President NNP PROPN
    2816 , , PUNCT
    2817 Dwight NNP PROPN
    2818 D. NNP PROPN
    2819 Eisenhower NNP PROPN
    2820 , , PUNCT
    2821 initiated VBD VERB
    2822 the DT DET
    2823 last JJ ADJ
    2824 truly RB ADV
    2825 great JJ ADJ
    2826 national JJ ADJ
    2827 infrastructure NN NOUN
    2828 program NN NOUN
    2829 — : PUNCT
    2830 the DT DET
    2831 building NN NOUN
    2832 of IN ADP
    2833 the DT DET
    2834 Interstate NNP PROPN
    2835 Highway NNP PROPN
    2836 System NNP PROPN
    2837 . . PUNCT
    2838 The DT DET
    2839 time NN NOUN
    2840 has VBZ AUX
    2841 come VBN VERB
    2842 for IN ADP
    2843 a DT DET
    2844 new JJ ADJ
    2845 program NN NOUN
    2846 of IN ADP
    2847 national JJ ADJ
    2848 rebuilding NN NOUN
    2849 . . PUNCT
    2850 America NNP PROPN
    2851 has VBZ AUX
    2852 spent VBN VERB
    2853 approximately RB ADV
    2854 $ $ SYM
    2855 6 CD NUM
    2856 trillion CD NUM
    2857 in IN ADP
    2858 the DT DET
    2859 Middle NNP PROPN
    2860 East NNP PROPN
    2861 ; : PUNCT
    2862 all PDT DET
    2863 the DT DET
    2864 while NN NOUN
    2865 , , PUNCT
    2866 our PRP$ PRON
    2867 infrastructure NN NOUN
    2868 at IN ADP
    2869 home NN NOUN
    2870 is VBZ AUX
    2871 crumbling VBG VERB
    2872 . . PUNCT
    2873 With IN ADP
    2874 this DT DET
    2875 $ $ SYM
    2876 6 CD NUM
    2877 trillion CD NUM
    2878 , , PUNCT
    2879 we PRP PRON
    2880 could MD AUX
    2881 have VB AUX
    2882 rebuilt VBN VERB
    2883 our PRP$ PRON
    2884 country NN NOUN
    2885 twice RB ADV
    2886 , , PUNCT
    2887 and CC CCONJ
    2888 maybe RB ADV
    2889 even RB ADV
    2890 three CD NUM
    2891 times NNS NOUN
    2892 if IN SCONJ
    2893 we PRP PRON
    2894 had VBD VERB
    2895 people NNS NOUN
    2896 who WP PRON
    2897 had VBD VERB
    2898 the DT DET
    2899 ability NN NOUN
    2900 to TO PART
    2901 negotiate VB VERB
    2902 . . PUNCT
    2903 [ XX X
    2904 Laughter XX X
    2905 ] -RRB- PUNCT
    2906

     _SP SPACE
    2907 To TO PART
    2908 launch VB VERB
    2909 our PRP$ PRON
    2910 national JJ ADJ
    2911 rebuilding NN NOUN
    2912 , , PUNCT
    2913 I PRP PRON
    2914 will MD AUX
    2915 be VB AUX
    2916 asking VBG VERB
    2917 Congress NNP PROPN
    2918 to TO PART
    2919 approve VB VERB
    2920 legislation NN NOUN
    2921 that WDT DET
    2922 produces VBZ VERB
    2923 a DT DET
    2924 $ $ SYM
    2925 1 CD NUM
    2926 trillion CD NUM
    2927 investment NN NOUN
    2928 in IN ADP
    2929 infrastructure NN NOUN
    2930 of IN ADP
    2931 the DT DET
    2932 United NNP PROPN
    2933 States NNP PROPN
    2934 — : PUNCT
    2935 financed VBN VERB
    2936 through IN ADP
    2937 both CC CCONJ
    2938 public JJ ADJ
    2939 and CC CCONJ
    2940 private JJ ADJ
    2941 capital NN NOUN
    2942 — : PUNCT
    2943 creating VBG VERB
    2944 millions NNS NOUN
    2945 of IN ADP
    2946 new JJ ADJ
    2947 jobs NNS NOUN
    2948 . . PUNCT
    2949 This DT DET
    2950 effort NN NOUN
    2951 will MD AUX
    2952 be VB AUX
    2953 guided VBN VERB
    2954 by IN ADP
    2955 two CD NUM
    2956 core NN NOUN
    2957 principles NNS NOUN
    2958 : : PUNCT
    2959 buy VB VERB
    2960 American JJ ADJ
    2961 and CC CCONJ
    2962 hire VB VERB
    2963 American JJ ADJ
    2964 . . PUNCT
    2965

     _SP SPACE
    2966 Tonight NN NOUN
    2967 I PRP PRON
    2968 am VBP AUX
    2969 also RB ADV
    2970 calling VBG VERB
    2971 on IN ADP
    2972 this DT DET
    2973 Congress NNP PROPN
    2974 to TO PART
    2975 repeal VB VERB
    2976 and CC CCONJ
    2977 replace VB VERB
    2978 Obamacare NNP PROPN
    2979 with IN ADP
    2980 reforms NNS NOUN
    2981 that WDT DET
    2982 expand VBP VERB
    2983 choice NN NOUN
    2984 , , PUNCT
    2985 increase VB VERB
    2986 access NN NOUN
    2987 , , PUNCT
    2988 lower JJR ADJ
    2989 costs NNS NOUN
    2990 , , PUNCT
    2991 and CC CCONJ
    2992 at IN ADP
    2993 the DT DET
    2994 same JJ ADJ
    2995 time NN NOUN
    2996 , , PUNCT
    2997 provide VB VERB
    2998 better JJR ADJ
    2999 health NN NOUN
    3000 care NN NOUN
    3001 . . PUNCT
    3002

     _SP SPACE
    3003 Mandating VBG VERB
    3004 every DT DET
    3005 American NNP PROPN
    3006 to TO PART
    3007 buy VB VERB
    3008 Government NN NOUN
    3009 - HYPH PUNCT
    3010 approved VBN VERB
    3011 health NN NOUN
    3012 insurance NN NOUN
    3013 was VBD AUX
    3014 never RB ADV
    3015 the DT DET
    3016 right JJ ADJ
    3017 solution NN NOUN
    3018 for IN ADP
    3019 our PRP$ PRON
    3020 country NN NOUN
    3021 . . PUNCT
    3022 The DT DET
    3023 way NN NOUN
    3024 to TO PART
    3025 make VB VERB
    3026 health NN NOUN
    3027 insurance NN NOUN
    3028 available JJ ADJ
    3029 to IN ADP
    3030 everyone NN PRON
    3031 is VBZ AUX
    3032 to TO PART
    3033 lower VB VERB
    3034 the DT DET
    3035 cost NN NOUN
    3036 of IN ADP
    3037 health NN NOUN
    3038 insurance NN NOUN
    3039 , , PUNCT
    3040 and CC CCONJ
    3041 that DT DET
    3042 is VBZ VERB
    3043 what WP PRON
    3044 we PRP PRON
    3045 are VBP AUX
    3046 going VBG VERB
    3047 do VB VERB
    3048 . . PUNCT
    3049

     _SP SPACE
    3050 Obamacare VBP VERB
    3051 premiums NNS NOUN
    3052 nationwide RB ADV
    3053 have VBP AUX
    3054 increased VBN VERB
    3055 by IN ADP
    3056 double JJ ADJ
    3057 and CC CCONJ
    3058 triple JJ ADJ
    3059 digits NNS NOUN
    3060 . . PUNCT
    3061 As IN ADP
    3062 an DT DET
    3063 example NN NOUN
    3064 , , PUNCT
    3065 Arizona NNP PROPN
    3066 went VBD VERB
    3067 up RB ADV
    3068 116 CD NUM
    3069 percent NN NOUN
    3070 last JJ ADJ
    3071 year NN NOUN
    3072 alone RB ADV
    3073 . . PUNCT
    3074 Governor NNP PROPN
    3075 Matt NNP PROPN
    3076 Bevin NNP PROPN
    3077 of IN ADP
    3078 Kentucky NNP PROPN
    3079 just RB ADV
    3080 said VBD VERB
    3081 Obamacare NNP PROPN
    3082 is VBZ AUX
    3083 failing VBG VERB
    3084 in IN ADP
    3085 his PRP$ PRON
    3086 State NNP PROPN
    3087 — : PUNCT
    3088 the DT DET
    3089 State NNP PROPN
    3090 of IN ADP
    3091 Kentucky NNP PROPN
    3092 — : PUNCT
    3093 and CC CCONJ
    3094 it PRP PRON
    3095 's VBZ VERB
    3096 unsustainable JJ ADJ
    3097 and CC CCONJ
    3098 collapsing VBG VERB
    3099 . . PUNCT
    3100

     _SP SPACE
    3101 One CD NUM
    3102 - HYPH PUNCT
    3103 third NN NOUN
    3104 of IN ADP
    3105 the DT DET
    3106 counties NNS NOUN
    3107 have VBP VERB
    3108 only RB ADV
    3109 one CD NUM
    3110 insurer NN NOUN
    3111 , , PUNCT
    3112 and CC CCONJ
    3113 they PRP PRON
    3114 are VBP AUX
    3115 losing VBG VERB
    3116 them PRP PRON
    3117 fast RB ADV
    3118 . . PUNCT
    3119 They PRP PRON
    3120 are VBP AUX
    3121 losing VBG VERB
    3122 them PRP PRON
    3123 so RB ADV
    3124 fast RB ADV
    3125 . . PUNCT
    3126 They PRP PRON
    3127 are VBP AUX
    3128 leaving VBG VERB
    3129 , , PUNCT
    3130 and CC CCONJ
    3131 many JJ ADJ
    3132 Americans NNPS PROPN
    3133 have VBP VERB
    3134 no DT DET
    3135 choice NN NOUN
    3136 at RB ADV
    3137 all RB ADV
    3138 . . PUNCT
    3139 There EX PRON
    3140 's VBZ AUX
    3141 no DT DET
    3142 choice NN NOUN
    3143 left VBN VERB
    3144 . . PUNCT
    3145 Remember VB VERB
    3146 when WRB ADV
    3147 you PRP PRON
    3148 were VBD AUX
    3149 told VBN VERB
    3150 that IN SCONJ
    3151 you PRP PRON
    3152 could MD AUX
    3153 keep VB VERB
    3154 your PRP$ PRON
    3155 doctor NN NOUN
    3156 and CC CCONJ
    3157 keep VB VERB
    3158 your PRP$ PRON
    3159 plan NN NOUN
    3160 ? . PUNCT
    3161 We PRP PRON
    3162 now RB ADV
    3163 know VBP VERB
    3164 that IN SCONJ
    3165 all DT DET
    3166 of IN ADP
    3167 those DT DET
    3168 promises NNS NOUN
    3169 have VBP AUX
    3170 been VBN AUX
    3171 totally RB ADV
    3172 broken VBN VERB
    3173 . . PUNCT
    3174 Obamacare NNP PROPN
    3175 is VBZ AUX
    3176 collapsing VBG VERB
    3177 , , PUNCT
    3178 and CC CCONJ
    3179 we PRP PRON
    3180 must MD AUX
    3181 act VB VERB
    3182 decisively RB ADV
    3183 to TO PART
    3184 protect VB VERB
    3185 all DT DET
    3186 Americans NNPS PROPN
    3187 . . PUNCT
    3188

     _SP SPACE
    3189 Action NNP PROPN
    3190 is VBZ AUX
    3191 not RB PART
    3192 a DT DET
    3193 choice NN NOUN
    3194 , , PUNCT
    3195 it PRP PRON
    3196 is VBZ AUX
    3197 a DT DET
    3198 necessity NN NOUN
    3199 . . PUNCT
    3200 So RB ADV
    3201 I PRP PRON
    3202 am VBP AUX
    3203 calling VBG VERB
    3204 on IN ADP
    3205 all DT DET
    3206 Democrats NNPS PROPN
    3207 and CC CCONJ
    3208 Republicans NNPS PROPN
    3209 in IN ADP
    3210 Congress NNP PROPN
    3211 to TO PART
    3212 work VB VERB
    3213 with IN ADP
    3214 us PRP PRON
    3215 to TO PART
    3216 save VB VERB
    3217 Americans NNPS PROPN
    3218 from IN ADP
    3219 this DT DET
    3220 imploding VBG VERB
    3221 Obamacare NNP PROPN
    3222 disaster NN NOUN
    3223 . . PUNCT
    3224

     _SP SPACE
    3225 Here RB ADV
    3226 are VBP AUX
    3227 the DT DET
    3228 principles NNS NOUN
    3229 that WDT DET
    3230 should MD AUX
    3231 guide VB VERB
    3232 the DT DET
    3233 Congress NNP PROPN
    3234 as IN ADP
    3235 we PRP PRON
    3236 move VBP VERB
    3237 to TO PART
    3238 create VB VERB
    3239 a DT DET
    3240 better JJR ADJ
    3241 health NN NOUN
    3242 care NN NOUN
    3243 system NN NOUN
    3244 for IN ADP
    3245 all DT DET
    3246 Americans NNPS PROPN
    3247 : : PUNCT
    3248

     _SP SPACE
    3249 First RB ADV
    3250 , , PUNCT
    3251 we PRP PRON
    3252 should MD AUX
    3253 ensure VB VERB
    3254 that IN SCONJ
    3255 Americans NNPS PROPN
    3256 with IN ADP
    3257 preexisting JJ ADJ
    3258 conditions NNS NOUN
    3259 have VBP VERB
    3260 access NN NOUN
    3261 to IN ADP
    3262 coverage NN NOUN
    3263 , , PUNCT
    3264 and CC CCONJ
    3265 that IN SCONJ
    3266 we PRP PRON
    3267 have VBP VERB
    3268 a DT DET
    3269 stable JJ ADJ
    3270 transition NN NOUN
    3271 for IN ADP
    3272 Americans NNPS PROPN
    3273 currently RB ADV
    3274 enrolled VBD VERB
    3275 in IN ADP
    3276 the DT DET
    3277 health NN NOUN
    3278 care NN NOUN
    3279 exchanges NNS NOUN
    3280 . . PUNCT
    3281

     _SP SPACE
    3282 Secondly RB ADV
    3283 , , PUNCT
    3284 we PRP PRON
    3285 should MD AUX
    3286 help VB VERB
    3287 Americans NNPS PROPN
    3288 purchase VB VERB
    3289 their PRP$ PRON
    3290 own JJ ADJ
    3291 coverage NN NOUN
    3292 through IN ADP
    3293 the DT DET
    3294 use NN NOUN
    3295 of IN ADP
    3296 tax NN NOUN
    3297 credits NNS NOUN
    3298 and CC CCONJ
    3299 expanded VBN VERB
    3300 health NN NOUN
    3301 savings NNS NOUN
    3302 accounts NNS NOUN
    3303 , , PUNCT
    3304 but CC CCONJ
    3305 it PRP PRON
    3306 must MD AUX
    3307 be VB VERB
    3308 the DT DET
    3309 plan NN NOUN
    3310 they PRP PRON
    3311 want VBP VERB
    3312 , , PUNCT
    3313 not RB PART
    3314 the DT DET
    3315 plan NN NOUN
    3316 forced VBN VERB
    3317 on IN ADP
    3318 them PRP PRON
    3319 by IN ADP
    3320 our PRP$ PRON
    3321 Government NNP PROPN
    3322 . . PUNCT
    3323

     _SP SPACE
    3324 Thirdly RB ADV
    3325 , , PUNCT
    3326 we PRP PRON
    3327 should MD AUX
    3328 give VB VERB
    3329 our PRP$ PRON
    3330 State NNP PROPN
    3331 Governors NNPS PROPN
    3332 the DT DET
    3333 resources NNS NOUN
    3334 and CC CCONJ
    3335 flexibility NN NOUN
    3336 they PRP PRON
    3337 need VBP VERB
    3338 with IN ADP
    3339 Medicaid NNP PROPN
    3340 to TO PART
    3341 make VB VERB
    3342 sure JJ ADJ
    3343 no DT DET
    3344 one NN NOUN
    3345 is VBZ AUX
    3346 left VBN VERB
    3347 out RP ADP
    3348 . . PUNCT
    3349

     _SP SPACE
    3350 Fourth JJ ADJ
    3351 , , PUNCT
    3352 we PRP PRON
    3353 should MD AUX
    3354 implement VB VERB
    3355 legal JJ ADJ
    3356 reforms NNS NOUN
    3357 that WDT DET
    3358 protect VBP VERB
    3359 patients NNS NOUN
    3360 and CC CCONJ
    3361 doctors NNS NOUN
    3362 from IN ADP
    3363 unnecessary JJ ADJ
    3364 costs NNS NOUN
    3365 that WDT DET
    3366 drive VBP VERB
    3367 up RP ADP
    3368 the DT DET
    3369 price NN NOUN
    3370 of IN ADP
    3371 insurance NN NOUN
    3372 and CC CCONJ
    3373 work NN NOUN
    3374 to TO PART
    3375 bring VB VERB
    3376 down RP ADP
    3377 the DT DET
    3378 artificially RB ADV
    3379 high JJ ADJ
    3380 price NN NOUN
    3381 of IN ADP
    3382 drugs NNS NOUN
    3383 and CC CCONJ
    3384 bring VB VERB
    3385 them PRP PRON
    3386 down RP ADP
    3387 immediately RB ADV
    3388 . . PUNCT
    3389 And CC CCONJ
    3390 finally RB ADV
    3391 , , PUNCT
    3392 the DT DET
    3393 time NN NOUN
    3394 has VBZ AUX
    3395 come VBN VERB
    3396 to TO PART
    3397 give VB VERB
    3398 Americans NNPS PROPN
    3399 the DT DET
    3400 freedom NN NOUN
    3401 to TO PART
    3402 purchase VB VERB
    3403 health NN NOUN
    3404 insurance NN NOUN
    3405 across IN ADP
    3406 State NNP PROPN
    3407 lines NNS NOUN
    3408 , , PUNCT
    3409 which WDT DET
    3410 will MD AUX
    3411 create VB VERB
    3412 a DT DET
    3413 truly RB ADV
    3414 competitive JJ ADJ
    3415 national JJ ADJ
    3416 marketplace NN NOUN
    3417 that WDT DET
    3418 will MD AUX
    3419 bring VB VERB
    3420 costs NNS NOUN
    3421 way NN NOUN
    3422 down RB ADV
    3423 and CC CCONJ
    3424 provide VB VERB
    3425 far RB ADV
    3426 better JJR ADJ
    3427 care NN NOUN
    3428 . . PUNCT
    3429 So RB ADV
    3430 important JJ ADJ
    3431 . . PUNCT
    3432

     _SP SPACE
    3433 Everything NN PRON
    3434 that WDT DET
    3435 is VBZ AUX
    3436 broken VBN VERB
    3437 in IN ADP
    3438 our PRP$ PRON
    3439 country NN NOUN
    3440 can MD AUX
    3441 be VB AUX
    3442 fixed VBN VERB
    3443 . . PUNCT
    3444 Every DT DET
    3445 problem NN NOUN
    3446 can MD AUX
    3447 be VB AUX
    3448 solved VBN VERB
    3449 . . PUNCT
    3450 And CC CCONJ
    3451 every DT DET
    3452 hurting VBG VERB
    3453 family NN NOUN
    3454 can MD AUX
    3455 find VB VERB
    3456 healing NN NOUN
    3457 and CC CCONJ
    3458 hope NN NOUN
    3459 . . PUNCT
    3460

     _SP SPACE
    3461 Our PRP$ PRON
    3462 citizens NNS NOUN
    3463 deserve VBP VERB
    3464 this DT DET
    3465 and CC CCONJ
    3466 so RB ADV
    3467 much RB ADV
    3468 more JJR ADJ
    3469 , , PUNCT
    3470 so CC CCONJ
    3471 why WRB ADV
    3472 not RB PART
    3473 join VB VERB
    3474 forces NNS NOUN
    3475 and CC CCONJ
    3476 finally RB ADV
    3477 get VB VERB
    3478 the DT DET
    3479 job NN NOUN
    3480 done VBN VERB
    3481 , , PUNCT
    3482 and CC CCONJ
    3483 get VB VERB
    3484 it PRP PRON
    3485 done VBN VERB
    3486 right RB ADV
    3487 ? . PUNCT
    3488 On IN ADP
    3489 this DT DET
    3490 and CC CCONJ
    3491 so RB ADV
    3492 many JJ ADJ
    3493 other JJ ADJ
    3494 things NNS NOUN
    3495 , , PUNCT
    3496 Democrats NNPS PROPN
    3497 and CC CCONJ
    3498 Republicans NNPS PROPN
    3499 should MD AUX
    3500 get VB VERB
    3501 together RB ADV
    3502 and CC CCONJ
    3503 unite VB VERB
    3504 for IN ADP
    3505 the DT DET
    3506 good NN NOUN
    3507 of IN ADP
    3508 our PRP$ PRON
    3509 country NN NOUN
    3510 and CC CCONJ
    3511 for IN ADP
    3512 the DT DET
    3513 good NN NOUN
    3514 of IN ADP
    3515 the DT DET
    3516 American JJ ADJ
    3517 people NNS NOUN
    3518 . . PUNCT
    3519

     _SP SPACE
    3520 My PRP$ PRON
    3521 administration NN NOUN
    3522 wants VBZ VERB
    3523 to TO PART
    3524 work VB VERB
    3525 with IN ADP
    3526 members NNS NOUN
    3527 of IN ADP
    3528 both DT DET
    3529 parties NNS NOUN
    3530 to TO PART
    3531 make VB VERB
    3532 childcare NN NOUN
    3533 accessible JJ ADJ
    3534 and CC CCONJ
    3535 affordable JJ ADJ
    3536 ; : PUNCT
    3537 to TO PART
    3538 help VB VERB
    3539 ensure VB VERB
    3540 new JJ ADJ
    3541 parents NNS NOUN
    3542 that WDT DET
    3543 they PRP PRON
    3544 have VBP AUX
    3545 paid VBN VERB
    3546 family NN NOUN
    3547 leave VB VERB
    3548 ; : PUNCT
    3549 to TO PART
    3550 invest VB VERB
    3551 in IN ADP
    3552 women NNS NOUN
    3553 's POS PART
    3554 health NN NOUN
    3555 ; : PUNCT
    3556 and CC CCONJ
    3557 to TO PART
    3558 promote VB VERB
    3559 clean JJ ADJ
    3560 air NN NOUN
    3561 and CC CCONJ
    3562 clean JJ ADJ
    3563 water NN NOUN
    3564 ; : PUNCT
    3565 and CC CCONJ
    3566 to TO PART
    3567 rebuild VB VERB
    3568 our PRP$ PRON
    3569 military NN NOUN
    3570 and CC CCONJ
    3571 our PRP$ PRON
    3572 infrastructure NN NOUN
    3573 . . PUNCT
    3574

     _SP SPACE
    3575 True JJ ADJ
    3576 love NN NOUN
    3577 for IN ADP
    3578 our PRP$ PRON
    3579 people NNS NOUN
    3580 requires VBZ VERB
    3581 us PRP PRON
    3582 to TO PART
    3583 find VB VERB
    3584 common JJ ADJ
    3585 ground NN NOUN
    3586 , , PUNCT
    3587 to TO PART
    3588 advance VB VERB
    3589 the DT DET
    3590 common JJ ADJ
    3591 good NN NOUN
    3592 , , PUNCT
    3593 and CC CCONJ
    3594 to TO PART
    3595 cooperate VB VERB
    3596 on IN ADP
    3597 behalf NN NOUN
    3598 of IN ADP
    3599 every DT DET
    3600 American JJ ADJ
    3601 child NN NOUN
    3602 who WP PRON
    3603 deserves VBZ VERB
    3604 a DT DET
    3605 much RB ADV
    3606 brighter JJR ADJ
    3607 future NN NOUN
    3608 . . PUNCT
    3609

     _SP SPACE
    3610 An DT DET
    3611 incredible JJ ADJ
    3612 young JJ ADJ
    3613 woman NN NOUN
    3614 is VBZ AUX
    3615 with IN ADP
    3616 us PRP PRON
    3617 this DT DET
    3618 evening NN NOUN
    3619 , , PUNCT
    3620 who WP PRON
    3621 should MD AUX
    3622 serve VB VERB
    3623 as IN ADP
    3624 an DT DET
    3625 inspiration NN NOUN
    3626 to IN ADP
    3627 us PRP PRON
    3628 all DT DET
    3629 . . PUNCT
    3630 Today NN NOUN
    3631 is VBZ AUX
    3632 Rare NNP PROPN
    3633 Disease NNP PROPN
    3634 Day NNP PROPN
    3635 , , PUNCT
    3636 and CC CCONJ
    3637 joining VBG VERB
    3638 us PRP PRON
    3639 in IN ADP
    3640 the DT DET
    3641 gallery NN NOUN
    3642 is VBZ VERB
    3643 a DT DET
    3644 rare JJ ADJ
    3645 disease NN NOUN
    3646 survivor NN NOUN
    3647 , , PUNCT
    3648 Megan NNP PROPN
    3649 Crowley NNP PROPN
    3650 . . PUNCT
    3651

     _SP SPACE
    3652 Megan NNP PROPN
    3653 was VBD AUX
    3654 diagnosed VBN VERB
    3655 with IN ADP
    3656 Pompe NNP PROPN
    3657 disease NN NOUN
    3658 , , PUNCT
    3659 a DT DET
    3660 rare JJ ADJ
    3661 and CC CCONJ
    3662 serious JJ ADJ
    3663 illness NN NOUN
    3664 , , PUNCT
    3665 when WRB ADV
    3666 she PRP PRON
    3667 was VBD VERB
    3668 15 CD NUM
    3669 months NNS NOUN
    3670 old JJ ADJ
    3671 . . PUNCT
    3672 She PRP PRON
    3673 was VBD AUX
    3674 not RB PART
    3675 expected VBN VERB
    3676 to TO PART
    3677 live VB VERB
    3678 past IN ADP
    3679 5 CD NUM
    3680 . . PUNCT
    3681 On IN ADP
    3682 receiving VBG VERB
    3683 this DT DET
    3684 news NN NOUN
    3685 , , PUNCT
    3686 Megan NNP PROPN
    3687 's POS PART
    3688 dad NN NOUN
    3689 John NNP PROPN
    3690 fought VBD VERB
    3691 with IN ADP
    3692 everything NN PRON
    3693 he PRP PRON
    3694 had VBD VERB
    3695 to TO PART
    3696 save VB VERB
    3697 the DT DET
    3698 life NN NOUN
    3699 of IN ADP
    3700 his PRP$ PRON
    3701 precious JJ ADJ
    3702 child NN NOUN
    3703 . . PUNCT
    3704 He PRP PRON
    3705 founded VBD VERB
    3706 a DT DET
    3707 company NN NOUN
    3708 to TO PART
    3709 look VB VERB
    3710 for IN ADP
    3711 a DT DET
    3712 cure NN NOUN
    3713 and CC CCONJ
    3714 helped VBD VERB
    3715 develop VB VERB
    3716 the DT DET
    3717 drug NN NOUN
    3718 that WDT DET
    3719 saved VBD VERB
    3720 Megan NNP PROPN
    3721 's POS PART
    3722 life NN NOUN
    3723 . . PUNCT
    3724 Today NN NOUN
    3725 she PRP PRON
    3726 is VBZ AUX
    3727 20 CD NUM
    3728 years NNS NOUN
    3729 old JJ ADJ
    3730 and CC CCONJ
    3731 a DT DET
    3732 sophomore NN NOUN
    3733 at IN ADP
    3734 Notre NNP PROPN
    3735 Dame NNP PROPN
    3736 . . PUNCT
    3737

     _SP SPACE
    3738 Megan NNP PROPN
    3739 's POS PART
    3740 story NN NOUN
    3741 is VBZ AUX
    3742 about IN ADP
    3743 the DT DET
    3744 unbounded JJ ADJ
    3745 power NN NOUN
    3746 of IN ADP
    3747 a DT DET
    3748 father NN NOUN
    3749 's POS PART
    3750 love NN NOUN
    3751 for IN ADP
    3752 a DT DET
    3753 daughter NN NOUN
    3754 . . PUNCT
    3755 But CC CCONJ
    3756 our PRP$ PRON
    3757 slow JJ ADJ
    3758 and CC CCONJ
    3759 burdensome JJ ADJ
    3760 approval NN NOUN
    3761 process NN NOUN
    3762 at IN ADP
    3763 the DT DET
    3764 Food NNP PROPN
    3765 and CC CCONJ
    3766 Drug NNP PROPN
    3767 Administration NNP PROPN
    3768 keeps VBZ VERB
    3769 too RB ADV
    3770 many JJ ADJ
    3771 advances NNS NOUN
    3772 , , PUNCT
    3773 like IN ADP
    3774 the DT DET
    3775 one NN NOUN
    3776 that WDT DET
    3777 saved VBD VERB
    3778 Megan NNP PROPN
    3779 's POS PART
    3780 life NN NOUN
    3781 , , PUNCT
    3782 from IN ADP
    3783 reaching VBG VERB
    3784 those DT DET
    3785 in IN ADP
    3786 need NN NOUN
    3787 . . PUNCT
    3788 If IN SCONJ
    3789 we PRP PRON
    3790 slash VBP VERB
    3791 the DT DET
    3792 restraints NNS NOUN
    3793 , , PUNCT
    3794 not RB PART
    3795 just RB ADV
    3796 at IN ADP
    3797 the DT DET
    3798 FDA NNP PROPN
    3799 , , PUNCT
    3800 but CC CCONJ
    3801 across IN ADP
    3802 our PRP$ PRON
    3803 Government NNP PROPN
    3804 , , PUNCT
    3805 then RB ADV
    3806 we PRP PRON
    3807 will MD AUX
    3808 be VB AUX
    3809 blessed VBN VERB
    3810 with IN ADP
    3811 far RB ADV
    3812 more JJR ADJ
    3813 miracles NNS NOUN
    3814 just RB ADV
    3815 like IN ADP
    3816 Megan NNP PROPN
    3817 . . PUNCT
    3818 In IN ADP
    3819 fact NN NOUN
    3820 , , PUNCT
    3821 our PRP$ PRON
    3822 children NNS NOUN
    3823 will MD AUX
    3824 grow VB VERB
    3825 up RP ADP
    3826 in IN ADP
    3827 a DT DET
    3828 nation NN NOUN
    3829 of IN ADP
    3830 miracles NNS NOUN
    3831 . . PUNCT
    3832

     _SP SPACE
    3833 But CC CCONJ
    3834 to TO PART
    3835 achieve VB VERB
    3836 this DT DET
    3837 future NN NOUN
    3838 , , PUNCT
    3839 we PRP PRON
    3840 must MD AUX
    3841 enrich VB VERB
    3842 the DT DET
    3843 mind NN NOUN
    3844 and CC CCONJ
    3845 the DT DET
    3846 souls NNS NOUN
    3847 of IN ADP
    3848 every DT DET
    3849 American JJ ADJ
    3850 child NN NOUN
    3851 . . PUNCT
    3852 Education NN NOUN
    3853 is VBZ AUX
    3854 the DT DET
    3855 civil JJ ADJ
    3856 rights NNS NOUN
    3857 issue NN NOUN
    3858 of IN ADP
    3859 our PRP$ PRON
    3860 time NN NOUN
    3861 . . PUNCT
    3862 I PRP PRON
    3863 am VBP AUX
    3864 calling VBG VERB
    3865 upon IN SCONJ
    3866 members NNS NOUN
    3867 of IN ADP
    3868 both DT DET
    3869 parties NNS NOUN
    3870 to TO PART
    3871 pass VB VERB
    3872 an DT DET
    3873 education NN NOUN
    3874 bill NN NOUN
    3875 that WDT DET
    3876 funds VBZ VERB
    3877 school NN NOUN
    3878 choice NN NOUN
    3879 for IN ADP
    3880 disadvantaged JJ ADJ
    3881 youth NN NOUN
    3882 , , PUNCT
    3883 including VBG VERB
    3884 millions NNS NOUN
    3885 of IN ADP
    3886 African JJ ADJ
    3887 American NNP PROPN
    3888 and CC CCONJ
    3889 Latino JJ ADJ
    3890 children NNS NOUN
    3891 . . PUNCT
    3892 These DT DET
    3893 families NNS NOUN
    3894 should MD AUX
    3895 be VB VERB
    3896 free JJ ADJ
    3897 to TO PART
    3898 choose VB VERB
    3899 the DT DET
    3900 public JJ ADJ
    3901 , , PUNCT
    3902 private JJ ADJ
    3903 , , PUNCT
    3904 charter NN NOUN
    3905 , , PUNCT
    3906 magnet NN NOUN
    3907 , , PUNCT
    3908 religious JJ ADJ
    3909 , , PUNCT
    3910 or CC CCONJ
    3911 home NN NOUN
    3912 school NN NOUN
    3913 that WDT DET
    3914 is VBZ VERB
    3915 right JJ ADJ
    3916 for IN ADP
    3917 them PRP PRON
    3918 . . PUNCT
    3919

     _SP SPACE
    3920 Joining VBG VERB
    3921 us PRP PRON
    3922 tonight NN NOUN
    3923 in IN ADP
    3924 the DT DET
    3925 gallery NN NOUN
    3926 is VBZ AUX
    3927 a DT DET
    3928 remarkable JJ ADJ
    3929 woman NN NOUN
    3930 , , PUNCT
    3931 Denisha NNP PROPN
    3932 Merriweather NNP PROPN
    3933 . . PUNCT
    3934 As IN ADP
    3935 a DT DET
    3936 young JJ ADJ
    3937 girl NN NOUN
    3938 , , PUNCT
    3939 Denisha NNP PROPN
    3940 struggled VBD VERB
    3941 in IN ADP
    3942 school NN NOUN
    3943 and CC CCONJ
    3944 failed VBN VERB
    3945 third JJ ADJ
    3946 grade NN NOUN
    3947 twice RB ADV
    3948 . . PUNCT
    3949 But CC CCONJ
    3950 then RB ADV
    3951 , , PUNCT
    3952 she PRP PRON
    3953 was VBD AUX
    3954 able JJ ADJ
    3955 to TO PART
    3956 enroll VB VERB
    3957 in IN ADP
    3958 a DT DET
    3959 private JJ ADJ
    3960 center NN NOUN
    3961 for IN ADP
    3962 learning NN NOUN
    3963 — : PUNCT
    3964 great JJ ADJ
    3965 learning NN NOUN
    3966 center NN NOUN
    3967 — : PUNCT
    3968 with IN ADP
    3969 the DT DET
    3970 help NN NOUN
    3971 of IN ADP
    3972 a DT DET
    3973 tax NN NOUN
    3974 credit NN NOUN
    3975 and CC CCONJ
    3976 a DT DET
    3977 scholarship NN NOUN
    3978 program NN NOUN
    3979 . . PUNCT
    3980

     _SP SPACE
    3981 Today NN NOUN
    3982 , , PUNCT
    3983 she PRP PRON
    3984 is VBZ AUX
    3985 the DT DET
    3986 first JJ ADJ
    3987 in IN ADP
    3988 her PRP$ PRON
    3989 family NN NOUN
    3990 to TO PART
    3991 graduate VB VERB
    3992 , , PUNCT
    3993 not RB PART
    3994 just RB ADV
    3995 from IN ADP
    3996 high JJ ADJ
    3997 school NN NOUN
    3998 , , PUNCT
    3999 but CC CCONJ
    4000 from IN ADP
    4001 college NN NOUN
    4002 . . PUNCT
    4003 Later RB ADV
    4004 this DT DET
    4005 year NN NOUN
    4006 she PRP PRON
    4007 will MD AUX
    4008 get VB VERB
    4009 her PRP$ PRON
    4010 master NN NOUN
    4011 's POS PART
    4012 degree NN NOUN
    4013 in IN ADP
    4014 social JJ ADJ
    4015 work NN NOUN
    4016 . . PUNCT
    4017 We PRP PRON
    4018 want VBP VERB
    4019 all DT DET
    4020 children NNS NOUN
    4021 to TO PART
    4022 be VB VERB
    4023 able JJ ADJ
    4024 to TO PART
    4025 break VB VERB
    4026 the DT DET
    4027 cycle NN NOUN
    4028 of IN ADP
    4029 poverty NN NOUN
    4030 just RB ADV
    4031 like IN ADP
    4032 Denisha NNP PROPN
    4033 . . PUNCT
    4034

     _SP SPACE
    4035 But CC CCONJ
    4036 to TO PART
    4037 break VB VERB
    4038 the DT DET
    4039 cycle NN NOUN
    4040 of IN ADP
    4041 poverty NN NOUN
    4042 , , PUNCT
    4043 we PRP PRON
    4044 must MD AUX
    4045 also RB ADV
    4046 break VB VERB
    4047 the DT DET
    4048 cycle NN NOUN
    4049 of IN ADP
    4050 violence NN NOUN
    4051 . . PUNCT
    4052 The DT DET
    4053 murder NN NOUN
    4054 rate NN NOUN
    4055 in IN ADP
    4056 2015 CD NUM
    4057 experienced VBD VERB
    4058 its PRP$ PRON
    4059 largest JJS ADJ
    4060 single JJ ADJ
    4061 - HYPH PUNCT
    4062 year NN NOUN
    4063 increase NN NOUN
    4064 in IN ADP
    4065 nearly RB ADV
    4066 half PDT DET
    4067 a DT DET
    4068 century NN NOUN
    4069 . . PUNCT
    4070 In IN ADP
    4071 Chicago NNP PROPN
    4072 , , PUNCT
    4073 more JJR ADJ
    4074 than IN SCONJ
    4075 4,000 CD NUM
    4076 people NNS NOUN
    4077 were VBD AUX
    4078 shot VBN VERB
    4079 last JJ ADJ
    4080 year NN NOUN
    4081 alone RB ADV
    4082 , , PUNCT
    4083 and CC CCONJ
    4084 the DT DET
    4085 murder NN NOUN
    4086 rate NN NOUN
    4087 so RB ADV
    4088 far RB ADV
    4089 this DT DET
    4090 year NN NOUN
    4091 has VBZ AUX
    4092 been VBN VERB
    4093 even RB ADV
    4094 higher JJR ADJ
    4095 . . PUNCT
    4096 This DT DET
    4097 is VBZ AUX
    4098 not RB PART
    4099 acceptable JJ ADJ
    4100 in IN ADP
    4101 our PRP$ PRON
    4102 society NN NOUN
    4103 . . PUNCT
    4104

     _SP SPACE
    4105 Every DT DET
    4106 American JJ ADJ
    4107 child NN NOUN
    4108 should MD AUX
    4109 be VB VERB
    4110 able JJ ADJ
    4111 to TO PART
    4112 grow VB VERB
    4113 up RP ADP
    4114 in IN ADP
    4115 a DT DET
    4116 safe JJ ADJ
    4117 community NN NOUN
    4118 , , PUNCT
    4119 to TO PART
    4120 attend VB VERB
    4121 a DT DET
    4122 great JJ ADJ
    4123 school NN NOUN
    4124 , , PUNCT
    4125 and CC CCONJ
    4126 to TO PART
    4127 have VB VERB
    4128 access NN NOUN
    4129 to IN ADP
    4130 a DT DET
    4131 high RB ADV
    4132 - HYPH PUNCT
    4133 paying VBG VERB
    4134 job NN NOUN
    4135 . . PUNCT
    4136 But CC CCONJ
    4137 to TO PART
    4138 create VB VERB
    4139 this DT DET
    4140 future NN NOUN
    4141 , , PUNCT
    4142 we PRP PRON
    4143 must MD AUX
    4144 work VB VERB
    4145 with IN ADP
    4146 , , PUNCT
    4147 not RB PART
    4148 against IN ADP
    4149 — : PUNCT
    4150 not RB PART
    4151 against IN ADP
    4152 — : PUNCT
    4153 the DT DET
    4154 men NNS NOUN
    4155 and CC CCONJ
    4156 women NNS NOUN
    4157 of IN ADP
    4158 law NN NOUN
    4159 enforcement NN NOUN
    4160 . . PUNCT
    4161 We PRP PRON
    4162 must MD AUX
    4163 build VB VERB
    4164 bridges NNS NOUN
    4165 of IN ADP
    4166 cooperation NN NOUN
    4167 and CC CCONJ
    4168 trust NN NOUN
    4169 , , PUNCT
    4170 not RB PART
    4171 drive VB VERB
    4172 the DT DET
    4173 wedge NN NOUN
    4174 of IN ADP
    4175 disunity NN NOUN
    4176 , , PUNCT
    4177 and CC CCONJ
    4178 really RB ADV
    4179 , , PUNCT
    4180 it PRP PRON
    4181 's VBZ VERB
    4182 what WP PRON
    4183 it PRP PRON
    4184 is VBZ AUX
    4185 — : PUNCT
    4186 division NN NOUN
    4187 . . PUNCT
    4188 It PRP PRON
    4189 's VBZ AUX
    4190 pure JJ ADJ
    4191 , , PUNCT
    4192 unadulterated JJ ADJ
    4193 division NN NOUN
    4194 . . PUNCT
    4195 We PRP PRON
    4196 have VBP VERB
    4197 to TO PART
    4198 unify VB VERB
    4199 . . PUNCT
    4200

     _SP SPACE
    4201 Police NNS NOUN
    4202 and CC CCONJ
    4203 sheriffs NNS NOUN
    4204 are VBP AUX
    4205 members NNS NOUN
    4206 of IN ADP
    4207 our PRP$ PRON
    4208 community NN NOUN
    4209 . . PUNCT
    4210 They PRP PRON
    4211 're VBP VERB
    4212 friends NNS NOUN
    4213 and CC CCONJ
    4214 neighbors NNS NOUN
    4215 , , PUNCT
    4216 they PRP PRON
    4217 're VBP VERB
    4218 mothers NNS NOUN
    4219 and CC CCONJ
    4220 fathers NNS NOUN
    4221 , , PUNCT
    4222 sons NNS NOUN
    4223 and CC CCONJ
    4224 daughters NNS NOUN
    4225 , , PUNCT
    4226 and CC CCONJ
    4227 they PRP PRON
    4228 leave VBP VERB
    4229 behind RB ADV
    4230 loved VBN VERB
    4231 ones NNS NOUN
    4232 every DT DET
    4233 day NN NOUN
    4234 who WP PRON
    4235 worry VBP VERB
    4236 about IN ADP
    4237 whether IN SCONJ
    4238 or CC CCONJ
    4239 not RB PART
    4240 they PRP PRON
    4241 'll MD AUX
    4242 come VB VERB
    4243 home RB ADV
    4244 safe JJ ADJ
    4245 and CC CCONJ
    4246 sound JJ ADJ
    4247 . . PUNCT
    4248 We PRP PRON
    4249 must MD AUX
    4250 support VB VERB
    4251 the DT DET
    4252 incredible JJ ADJ
    4253 men NNS NOUN
    4254 and CC CCONJ
    4255 women NNS NOUN
    4256 of IN ADP
    4257 law NN NOUN
    4258 enforcement NN NOUN
    4259 . . PUNCT
    4260

     _SP SPACE
    4261 And CC CCONJ
    4262 we PRP PRON
    4263 must MD AUX
    4264 support VB VERB
    4265 the DT DET
    4266 victims NNS NOUN
    4267 of IN ADP
    4268 crime NN NOUN
    4269 . . PUNCT
    4270 I PRP PRON
    4271 have VBP AUX
    4272 ordered VBN VERB
    4273 the DT DET
    4274 Department NNP PROPN
    4275 of IN ADP
    4276 Homeland NNP PROPN
    4277 Security NNP PROPN
    4278 to TO PART
    4279 create VB VERB
    4280 an DT DET
    4281 office NN NOUN
    4282 to TO PART
    4283 serve VB VERB
    4284 American JJ ADJ
    4285 victims NNS NOUN
    4286 . . PUNCT
    4287 The DT DET
    4288 office NN NOUN
    4289 is VBZ AUX
    4290 called VBN VERB
    4291 VOICE NN NOUN
    4292 : : PUNCT
    4293 Victims NNS NOUN
    4294 of IN ADP
    4295 Immigration NNP PROPN
    4296 Crime NNP PROPN
    4297 Engagement NNP PROPN
    4298 . . PUNCT
    4299 We PRP PRON
    4300 are VBP AUX
    4301 providing VBG VERB
    4302 a DT DET
    4303 voice NN NOUN
    4304 to IN ADP
    4305 those DT DET
    4306 who WP PRON
    4307 have VBP AUX
    4308 been VBN AUX
    4309 ignored VBN VERB
    4310 by IN ADP
    4311 our PRP$ PRON
    4312 media NNS NOUN
    4313 and CC CCONJ
    4314 silenced VBN VERB
    4315 by IN ADP
    4316 special JJ ADJ
    4317 interests NNS NOUN
    4318 . . PUNCT
    4319 Joining VBG VERB
    4320 us PRP PRON
    4321 in IN ADP
    4322 the DT DET
    4323 audience NN NOUN
    4324 tonight NN NOUN
    4325 are VBP AUX
    4326 four CD NUM
    4327 very RB ADV
    4328 brave JJ ADJ
    4329 Americans NNPS PROPN
    4330 whose WP$ DET
    4331 Government NNP PROPN
    4332 failed VBD VERB
    4333 them PRP PRON
    4334 . . PUNCT
    4335 Their PRP$ PRON
    4336 names NNS NOUN
    4337 are VBP AUX
    4338 Jamiel NNP PROPN
    4339 Shaw NNP PROPN
    4340 , , PUNCT
    4341 Susan NNP PROPN
    4342 Oliver NNP PROPN
    4343 , , PUNCT
    4344 Jenna NNP PROPN
    4345 Oliver NNP PROPN
    4346 , , PUNCT
    4347 and CC CCONJ
    4348 Jessica NNP PROPN
    4349 Davis NNP PROPN
    4350 . . PUNCT
    4351

     _SP SPACE
    4352 Jamiel NNP PROPN
    4353 's POS PART
    4354 17 CD NUM
    4355 - HYPH PUNCT
    4356 year NN NOUN
    4357 - HYPH PUNCT
    4358 old JJ ADJ
    4359 son NN NOUN
    4360 was VBD AUX
    4361 viciously RB ADV
    4362 murdered VBN VERB
    4363 by IN ADP
    4364 an DT DET
    4365 illegal JJ ADJ
    4366 immigrant JJ ADJ
    4367 gang NN NOUN
    4368 member NN NOUN
    4369 who WP PRON
    4370 had VBD AUX
    4371 just RB ADV
    4372 been VBN AUX
    4373 released VBN VERB
    4374 from IN ADP
    4375 prison NN NOUN
    4376 . . PUNCT
    4377 Jamiel NNP PROPN
    4378 Shaw NNP PROPN
    4379 , , PUNCT
    4380 Jr. NNP PROPN
    4381 was VBD AUX
    4382 an DT DET
    4383 incredible JJ ADJ
    4384 young JJ ADJ
    4385 man NN NOUN
    4386 , , PUNCT
    4387 with IN ADP
    4388 unlimited JJ ADJ
    4389 potential NN NOUN
    4390 , , PUNCT
    4391 who WP PRON
    4392 was VBD AUX
    4393 getting VBG VERB
    4394 ready JJ ADJ
    4395 to TO PART
    4396 go VB VERB
    4397 to IN ADP
    4398 college NN NOUN
    4399 where WRB ADV
    4400 he PRP PRON
    4401 would MD AUX
    4402 have VB AUX
    4403 excelled VBN VERB
    4404 as IN ADP
    4405 a DT DET
    4406 great JJ ADJ
    4407 college NN NOUN
    4408 quarterback NN NOUN
    4409 . . PUNCT
    4410 But CC CCONJ
    4411 he PRP PRON
    4412 never RB ADV
    4413 got VBD VERB
    4414 the DT DET
    4415 chance NN NOUN
    4416 . . PUNCT
    4417 His PRP$ PRON
    4418 father NN NOUN
    4419 , , PUNCT
    4420 who WP PRON
    4421 is VBZ VERB
    4422 in IN ADP
    4423 the DT DET
    4424 audience NN NOUN
    4425 tonight NN NOUN
    4426 , , PUNCT
    4427 has VBZ AUX
    4428 become VBN VERB
    4429 a DT DET
    4430 very RB ADV
    4431 good JJ ADJ
    4432 friend NN NOUN
    4433 of IN ADP
    4434 mine NN NOUN
    4435 . . PUNCT
    4436 Jamiel NNP PROPN
    4437 , , PUNCT
    4438 thank VBP VERB
    4439 you PRP PRON
    4440 . . PUNCT
    4441 Thank VBP VERB
    4442 you PRP PRON
    4443 . . PUNCT
    4444

     _SP SPACE
    4445 Also RB ADV
    4446 with IN ADP
    4447 us PRP PRON
    4448 are VBP AUX
    4449 Susan NNP PROPN
    4450 Oliver NNP PROPN
    4451 and CC CCONJ
    4452 Jessica NNP PROPN
    4453 Davis NNP PROPN
    4454 . . PUNCT
    4455 Their PRP$ PRON
    4456 husbands NNS NOUN
    4457 , , PUNCT
    4458 Deputy NNP PROPN
    4459 Sheriff NNP PROPN
    4460 Danny NNP PROPN
    4461 Oliver NNP PROPN
    4462 and CC CCONJ
    4463 Detective NNP PROPN
    4464 Michael NNP PROPN
    4465 Davis NNP PROPN
    4466 , , PUNCT
    4467 were VBD AUX
    4468 slain VBN VERB
    4469 in IN ADP
    4470 the DT DET
    4471 line NN NOUN
    4472 of IN ADP
    4473 duty NN NOUN
    4474 in IN ADP
    4475 California NNP PROPN
    4476 . . PUNCT
    4477 They PRP PRON
    4478 were VBD AUX
    4479 pillars NNS NOUN
    4480 of IN ADP
    4481 their PRP$ PRON
    4482 community NN NOUN
    4483 . . PUNCT
    4484 These DT DET
    4485 brave JJ ADJ
    4486 men NNS NOUN
    4487 were VBD AUX
    4488 viciously RB ADV
    4489 gunned VBN VERB
    4490 down RP ADP
    4491 by IN ADP
    4492 an DT DET
    4493 illegal JJ ADJ
    4494 immigrant NN NOUN
    4495 with IN ADP
    4496 a DT DET
    4497 criminal JJ ADJ
    4498 record NN NOUN
    4499 and CC CCONJ
    4500 two CD NUM
    4501 prior JJ ADJ
    4502 deportations NNS NOUN
    4503 . . PUNCT
    4504 Should MD AUX
    4505 have VB AUX
    4506 never RB ADV
    4507 been VBN VERB
    4508 in IN ADP
    4509 our PRP$ PRON
    4510 country NN NOUN
    4511 . . PUNCT
    4512

     _SP SPACE
    4513 Sitting VBG VERB
    4514 with IN ADP
    4515 Susan NNP PROPN
    4516 is VBZ AUX
    4517 her PRP$ PRON
    4518 daughter NN NOUN
    4519 , , PUNCT
    4520 Jenna NNP PROPN
    4521 . . PUNCT
    4522 Jenna NNP PROPN
    4523 , , PUNCT
    4524 I PRP PRON
    4525 want VBP VERB
    4526 you PRP PRON
    4527 to TO PART
    4528 know VB VERB
    4529 that IN SCONJ
    4530 your PRP$ PRON
    4531 father NN NOUN
    4532 was VBD AUX
    4533 a DT DET
    4534 hero NN NOUN
    4535 , , PUNCT
    4536 and CC CCONJ
    4537 that IN SCONJ
    4538 tonight NN NOUN
    4539 you PRP PRON
    4540 have VBP VERB
    4541 the DT DET
    4542 love NN NOUN
    4543 of IN ADP
    4544 an DT DET
    4545 entire JJ ADJ
    4546 country NN NOUN
    4547 supporting VBG VERB
    4548 you PRP PRON
    4549 and CC CCONJ
    4550 praying VBG VERB
    4551 for IN ADP
    4552 you PRP PRON
    4553 . . PUNCT
    4554

     _SP SPACE
    4555 To IN ADP
    4556 Jamiel NNP PROPN
    4557 , , PUNCT
    4558 Jenna NNP PROPN
    4559 , , PUNCT
    4560 Susan NNP PROPN
    4561 , , PUNCT
    4562 and CC CCONJ
    4563 Jessica NNP PROPN
    4564 : : PUNCT
    4565 I PRP PRON
    4566 want VBP VERB
    4567 you PRP PRON
    4568 to TO PART
    4569 know VB VERB
    4570 that IN SCONJ
    4571 we PRP PRON
    4572 will MD AUX
    4573 never RB ADV
    4574 stop VB VERB
    4575 fighting VBG VERB
    4576 for IN ADP
    4577 justice NN NOUN
    4578 . . PUNCT
    4579 Your PRP$ PRON
    4580 loved VBN VERB
    4581 ones NNS NOUN
    4582 will MD AUX
    4583 never RB ADV
    4584 , , PUNCT
    4585 ever RB ADV
    4586 be VB AUX
    4587 forgotten VBN VERB
    4588 . . PUNCT
    4589 We PRP PRON
    4590 will MD AUX
    4591 always RB ADV
    4592 honor VB VERB
    4593 their PRP$ PRON
    4594 memory NN NOUN
    4595 . . PUNCT
    4596

     _SP SPACE
    4597 Finally RB ADV
    4598 , , PUNCT
    4599 to TO PART
    4600 keep VB VERB
    4601 America NNP PROPN
    4602 safe JJ ADJ
    4603 , , PUNCT
    4604 we PRP PRON
    4605 must MD AUX
    4606 provide VB VERB
    4607 the DT DET
    4608 men NNS NOUN
    4609 and CC CCONJ
    4610 women NNS NOUN
    4611 of IN ADP
    4612 the DT DET
    4613 United NNP PROPN
    4614 States NNP PROPN
    4615 military NN NOUN
    4616 with IN ADP
    4617 the DT DET
    4618 tools NNS NOUN
    4619 they PRP PRON
    4620 need VBP VERB
    4621 to TO PART
    4622 prevent VB VERB
    4623 war NN NOUN
    4624 . . PUNCT
    4625 If IN SCONJ
    4626 they PRP PRON
    4627 must MD AUX
    4628 , , PUNCT
    4629 they PRP PRON
    4630 have VBP VERB
    4631 to TO PART
    4632 fight VB VERB
    4633 and CC CCONJ
    4634 they PRP PRON
    4635 only RB ADV
    4636 have VBP VERB
    4637 to TO PART
    4638 win VB VERB
    4639 . . PUNCT
    4640

     _SP SPACE
    4641 I PRP PRON
    4642 am VBP AUX
    4643 sending VBG VERB
    4644 Congress NNP PROPN
    4645 a DT DET
    4646 budget NN NOUN
    4647 that WDT DET
    4648 rebuilds VBZ VERB
    4649 the DT DET
    4650 military NN NOUN
    4651 , , PUNCT
    4652 eliminates VBZ VERB
    4653 the DT DET
    4654 defense NN NOUN
    4655 sequester NN NOUN
    4656 , , PUNCT
    4657 and CC CCONJ
    4658 calls VBZ VERB
    4659 for IN ADP
    4660 one CD NUM
    4661 of IN ADP
    4662 the DT DET
    4663 largest JJS ADJ
    4664 increases NNS NOUN
    4665 in IN ADP
    4666 national JJ ADJ
    4667 defense NN NOUN
    4668 spending NN NOUN
    4669 in IN ADP
    4670 American JJ ADJ
    4671 history NN NOUN
    4672 . . PUNCT
    4673 My PRP$ PRON
    4674 budget NN NOUN
    4675 will MD AUX
    4676 also RB ADV
    4677 increase VB VERB
    4678 funding NN NOUN
    4679 for IN ADP
    4680 our PRP$ PRON
    4681 veterans NNS NOUN
    4682 . . PUNCT
    4683 Our PRP$ PRON
    4684 veterans NNS NOUN
    4685 have VBP AUX
    4686 delivered VBN VERB
    4687 for IN ADP
    4688 this DT DET
    4689 Nation NN NOUN
    4690 , , PUNCT
    4691 and CC CCONJ
    4692 now RB ADV
    4693 we PRP PRON
    4694 must MD AUX
    4695 deliver VB VERB
    4696 for IN ADP
    4697 them PRP PRON
    4698 . . PUNCT
    4699

     _SP SPACE
    4700 The DT DET
    4701 challenges NNS NOUN
    4702 we PRP PRON
    4703 face VBP VERB
    4704 as IN ADP
    4705 a DT DET
    4706 nation NN NOUN
    4707 are VBP AUX
    4708 great JJ ADJ
    4709 , , PUNCT
    4710 but CC CCONJ
    4711 our PRP$ PRON
    4712 people NNS NOUN
    4713 are VBP VERB
    4714 even RB ADV
    4715 greater JJR ADJ
    4716 . . PUNCT
    4717 And CC CCONJ
    4718 none NN NOUN
    4719 are VBP AUX
    4720 greater JJR ADJ
    4721 or CC CCONJ
    4722 are VBP VERB
    4723 braver JJ ADJ
    4724 than IN SCONJ
    4725 those DT DET
    4726 who WP PRON
    4727 fight VBP VERB
    4728 for IN ADP
    4729 America NNP PROPN
    4730 in IN ADP
    4731 uniform NN NOUN
    4732 . . PUNCT
    4733

     _SP SPACE
    4734 We PRP PRON
    4735 are VBP AUX
    4736 blessed VBN VERB
    4737 to TO PART
    4738 be VB AUX
    4739 joined VBN VERB
    4740 tonight NN NOUN
    4741 by IN ADP
    4742 Carryn NNP PROPN
    4743 Owens NNP PROPN
    4744 , , PUNCT
    4745 the DT DET
    4746 widow NN NOUN
    4747 of IN ADP
    4748 U.S. NNP PROPN
    4749 Navy NNP PROPN
    4750 Special NNP PROPN
    4751 Operator NNP PROPN
    4752 , , PUNCT
    4753 Senior NNP PROPN
    4754 Chief NNP PROPN
    4755 William NNP PROPN
    4756 " `` PUNCT
    4757 Ryan NNP PROPN
    4758 " '' PUNCT
    4759 Owens NNP PROPN
    4760 . . PUNCT
    4761 Ryan NNP PROPN
    4762 died VBD VERB
    4763 as IN ADP
    4764 he PRP PRON
    4765 lived VBD VERB
    4766 : : PUNCT
    4767 a DT DET
    4768 warrior NN NOUN
    4769 and CC CCONJ
    4770 a DT DET
    4771 hero NN NOUN
    4772 , , PUNCT
    4773 battling VBG VERB
    4774 against IN ADP
    4775 terrorism NN NOUN
    4776 and CC CCONJ
    4777 securing VBG VERB
    4778 our PRP$ PRON
    4779 Nation NN NOUN
    4780 . . PUNCT
    4781 I PRP PRON
    4782 just RB ADV
    4783 spoke VBD VERB
    4784 to IN ADP
    4785 our PRP$ PRON
    4786 great JJ ADJ
    4787 General NNP PROPN
    4788 Mattis NNP PROPN
    4789 , , PUNCT
    4790 just RB ADV
    4791 now RB ADV
    4792 , , PUNCT
    4793 who WP PRON
    4794 reconfirmed VBD VERB
    4795 that DT DET
    4796 — : PUNCT
    4797 and CC CCONJ
    4798 I PRP PRON
    4799 quote—"Ryan VBP VERB
    4800 was VBD VERB
    4801 a DT DET
    4802 part NN NOUN
    4803 of IN ADP
    4804 a DT DET
    4805 highly RB ADV
    4806 successful JJ ADJ
    4807 raid NN NOUN
    4808 that WDT DET
    4809 generated VBD VERB
    4810 large JJ ADJ
    4811 amounts NNS NOUN
    4812 of IN ADP
    4813 vital JJ ADJ
    4814 intelligence NN NOUN
    4815 that WDT DET
    4816 will MD AUX
    4817 lead VB VERB
    4818 to IN ADP
    4819 many JJ ADJ
    4820 more JJR ADJ
    4821 victories NNS NOUN
    4822 in IN ADP
    4823 the DT DET
    4824 future NN NOUN
    4825 against IN ADP
    4826 our PRP$ PRON
    4827 enemy NN NOUN
    4828 . . PUNCT
    4829 " '' PUNCT
    4830 Ryan NNP PROPN
    4831 's POS PART
    4832 legacy NN NOUN
    4833 is VBZ AUX
    4834 etched VBN VERB
    4835 into IN ADP
    4836 eternity NN NOUN
    4837 . . PUNCT
    4838 Thank VBP VERB
    4839 you PRP PRON
    4840 . . PUNCT
    4841 [ XX X
    4842 Applause XX X
    4843 ] -RRB- PUNCT
    4844 And CC CCONJ
    4845 Ryan NNP PROPN
    4846 is VBZ AUX
    4847 looking VBG VERB
    4848 down RP ADP
    4849 , , PUNCT
    4850 right RB ADV
    4851 now RB ADV
    4852 — : PUNCT
    4853 you PRP PRON
    4854 know VBP VERB
    4855 that DT DET
    4856 — : PUNCT
    4857 and CC CCONJ
    4858 he PRP PRON
    4859 is VBZ VERB
    4860 very RB ADV
    4861 happy JJ ADJ
    4862 because IN SCONJ
    4863 I PRP PRON
    4864 think VBP VERB
    4865 he PRP PRON
    4866 just RB ADV
    4867 broke VBD VERB
    4868 a DT DET
    4869 record NN NOUN
    4870 . . PUNCT
    4871 [ XX X
    4872 Laughter XX X
    4873 ] -RRB- PUNCT
    4874

     _SP SPACE
    4875 For IN ADP
    4876 as IN ADP
    4877 the DT DET
    4878 Bible NNP PROPN
    4879 teaches VBZ VERB
    4880 us PRP PRON
    4881 , , PUNCT
    4882 there EX PRON
    4883 is VBZ AUX
    4884 no DT DET
    4885 greater JJR ADJ
    4886 act NN NOUN
    4887 of IN ADP
    4888 love NN NOUN
    4889 than IN SCONJ
    4890 to TO PART
    4891 lay VB VERB
    4892 down RP ADP
    4893 one NN NOUN
    4894 's POS PART
    4895 life NN NOUN
    4896 for IN ADP
    4897 one PRP PRON
    4898 's POS PART
    4899 friends NNS NOUN
    4900 . . PUNCT
    4901 Ryan NNP PROPN
    4902 laid VBD VERB
    4903 down RP ADP
    4904 his PRP$ PRON
    4905 life NN NOUN
    4906 for IN ADP
    4907 his PRP$ PRON
    4908 friends NNS NOUN
    4909 , , PUNCT
    4910 for IN ADP
    4911 his PRP$ PRON
    4912 country NN NOUN
    4913 , , PUNCT
    4914 and CC CCONJ
    4915 for IN ADP
    4916 our PRP$ PRON
    4917 freedom NN NOUN
    4918 . . PUNCT
    4919 And CC CCONJ
    4920 we PRP PRON
    4921 will MD AUX
    4922 never RB ADV
    4923 forget VB VERB
    4924 Ryan NNP PROPN
    4925 . . PUNCT
    4926

     _SP SPACE
    4927 To IN ADP
    4928 those DT DET
    4929 allies NNS NOUN
    4930 who WP PRON
    4931 wonder VBP VERB
    4932 what WP PRON
    4933 kind NN NOUN
    4934 of IN ADP
    4935 a DT DET
    4936 friend NN NOUN
    4937 America NNP PROPN
    4938 will MD AUX
    4939 be VB VERB
    4940 , , PUNCT
    4941 look VB VERB
    4942 no RB ADV
    4943 further RB ADV
    4944 than IN SCONJ
    4945 the DT DET
    4946 heroes NNS NOUN
    4947 who WP PRON
    4948 wear VBP VERB
    4949 our PRP$ PRON
    4950 uniform NN NOUN
    4951 . . PUNCT
    4952 Our PRP$ PRON
    4953 foreign JJ ADJ
    4954 policy NN NOUN
    4955 calls VBZ VERB
    4956 for IN ADP
    4957 a DT DET
    4958 direct JJ ADJ
    4959 , , PUNCT
    4960 robust JJ ADJ
    4961 , , PUNCT
    4962 and CC CCONJ
    4963 meaningful JJ ADJ
    4964 engagement NN NOUN
    4965 with IN ADP
    4966 the DT DET
    4967 world NN NOUN
    4968 . . PUNCT
    4969 It PRP PRON
    4970 is VBZ AUX
    4971 American JJ ADJ
    4972 leadership NN NOUN
    4973 based VBN VERB
    4974 on IN ADP
    4975 vital JJ ADJ
    4976 security NN NOUN
    4977 interests NNS NOUN
    4978 that WDT DET
    4979 we PRP PRON
    4980 share VBP VERB
    4981 with IN ADP
    4982 our PRP$ PRON
    4983 allies NNS NOUN
    4984 all RB ADV
    4985 across IN ADP
    4986 the DT DET
    4987 globe NN NOUN
    4988 . . PUNCT
    4989

     _SP SPACE
    4990 We PRP PRON
    4991 strongly RB ADV
    4992 support VBP VERB
    4993 NATO NNP PROPN
    4994 , , PUNCT
    4995 an DT DET
    4996 alliance NN NOUN
    4997 forged VBD VERB
    4998 through IN ADP
    4999 the DT DET
    5000 bonds NNS NOUN
    5001 of IN ADP
    5002 two CD NUM
    5003 world NN NOUN
    5004 wars NNS NOUN
    5005 that WDT DET
    5006 dethroned VBD VERB
    5007 fascism NN NOUN
    5008 , , PUNCT
    5009 and CC CCONJ
    5010 a DT DET
    5011 cold JJ ADJ
    5012 war NN NOUN
    5013 , , PUNCT
    5014 and CC CCONJ
    5015 defeated VBD VERB
    5016 communism NN NOUN
    5017 . . PUNCT
    5018

     _SP SPACE
    5019 But CC CCONJ
    5020 our PRP$ PRON
    5021 partners NNS NOUN
    5022 must MD AUX
    5023 meet VB VERB
    5024 their PRP$ PRON
    5025 financial JJ ADJ
    5026 obligations NNS NOUN
    5027 . . PUNCT
    5028 And CC CCONJ
    5029 now RB ADV
    5030 , , PUNCT
    5031 based VBN VERB
    5032 on IN ADP
    5033 our PRP$ PRON
    5034 very RB ADV
    5035 strong JJ ADJ
    5036 and CC CCONJ
    5037 frank JJ ADJ
    5038 discussions NNS NOUN
    5039 , , PUNCT
    5040 they PRP PRON
    5041 are VBP AUX
    5042 beginning VBG VERB
    5043 to TO PART
    5044 do VB VERB
    5045 just RB ADV
    5046 that DT DET
    5047 . . PUNCT
    5048 In IN ADP
    5049 fact NN NOUN
    5050 , , PUNCT
    5051 I PRP PRON
    5052 can MD AUX
    5053 tell VB VERB
    5054 you PRP PRON
    5055 , , PUNCT
    5056 the DT DET
    5057 money NN NOUN
    5058 is VBZ AUX
    5059 pouring VBG VERB
    5060 in RP ADP
    5061 . . PUNCT
    5062 Very RB ADV
    5063 nice JJ ADJ
    5064 . . PUNCT
    5065 We PRP PRON
    5066 expect VBP VERB
    5067 our PRP$ PRON
    5068 partners NNS NOUN
    5069 — : PUNCT
    5070 whether IN SCONJ
    5071 in IN ADP
    5072 NATO NNP PROPN
    5073 , , PUNCT
    5074 the DT DET
    5075 Middle NNP PROPN
    5076 East NNP PROPN
    5077 , , PUNCT
    5078 or CC CCONJ
    5079 in IN ADP
    5080 the DT DET
    5081 Pacific NNP PROPN
    5082 — : PUNCT
    5083 to TO PART
    5084 take VB VERB
    5085 a DT DET
    5086 direct JJ ADJ
    5087 and CC CCONJ
    5088 meaningful JJ ADJ
    5089 role NN NOUN
    5090 in IN ADP
    5091 both CC CCONJ
    5092 strategic JJ ADJ
    5093 and CC CCONJ
    5094 military JJ ADJ
    5095 operations NNS NOUN
    5096 , , PUNCT
    5097 and CC CCONJ
    5098 pay VB VERB
    5099 their PRP$ PRON
    5100 fair JJ ADJ
    5101 share NN NOUN
    5102 of IN ADP
    5103 the DT DET
    5104 cost NN NOUN
    5105 . . PUNCT
    5106 Have VB VERB
    5107 to TO PART
    5108 do VB VERB
    5109 that DT DET
    5110 . . PUNCT
    5111

     _SP SPACE
    5112 We PRP PRON
    5113 will MD AUX
    5114 respect VB VERB
    5115 historic JJ ADJ
    5116 institutions NNS NOUN
    5117 , , PUNCT
    5118 but CC CCONJ
    5119 we PRP PRON
    5120 will MD AUX
    5121 respect VB VERB
    5122 the DT DET
    5123 foreign JJ ADJ
    5124 rights NNS NOUN
    5125 of IN ADP
    5126 all DT DET
    5127 nations NNS NOUN
    5128 , , PUNCT
    5129 and CC CCONJ
    5130 they PRP PRON
    5131 have VBP VERB
    5132 to TO PART
    5133 respect VB VERB
    5134 our PRP$ PRON
    5135 rights NNS NOUN
    5136 as IN ADP
    5137 a DT DET
    5138 nation NN NOUN
    5139 also RB ADV
    5140 . . PUNCT
    5141 Free JJ ADJ
    5142 nations NNS NOUN
    5143 are VBP AUX
    5144 the DT DET
    5145 best JJS ADJ
    5146 vehicle NN NOUN
    5147 for IN ADP
    5148 expressing VBG VERB
    5149 the DT DET
    5150 will NN NOUN
    5151 of IN ADP
    5152 the DT DET
    5153 people NNS NOUN
    5154 , , PUNCT
    5155 and CC CCONJ
    5156 America NNP PROPN
    5157 respects VBZ VERB
    5158 the DT DET
    5159 right NN NOUN
    5160 of IN ADP
    5161 all DT DET
    5162 nations NNS NOUN
    5163 to TO PART
    5164 chart VB VERB
    5165 their PRP$ PRON
    5166 own JJ ADJ
    5167 path NN NOUN
    5168 . . PUNCT
    5169 My PRP$ PRON
    5170 job NN NOUN
    5171 is VBZ AUX
    5172 not RB PART
    5173 to TO PART
    5174 represent VB VERB
    5175 the DT DET
    5176 world NN NOUN
    5177 . . PUNCT
    5178 My PRP$ PRON
    5179 job NN NOUN
    5180 is VBZ AUX
    5181 to TO PART
    5182 represent VB VERB
    5183 the DT DET
    5184 United NNP PROPN
    5185 States NNP PROPN
    5186 of IN ADP
    5187 America NNP PROPN
    5188 . . PUNCT
    5189

     _SP SPACE
    5190 But CC CCONJ
    5191 we PRP PRON
    5192 know VBP VERB
    5193 that IN SCONJ
    5194 America NNP PROPN
    5195 is VBZ AUX
    5196 better JJR ADJ
    5197 off RP ADP
    5198 when WRB ADV
    5199 there EX PRON
    5200 is VBZ VERB
    5201 less JJR ADJ
    5202 conflict NN NOUN
    5203 , , PUNCT
    5204 not RB PART
    5205 more JJR ADJ
    5206 . . PUNCT
    5207 We PRP PRON
    5208 must MD AUX
    5209 learn VB VERB
    5210 from IN ADP
    5211 the DT DET
    5212 mistakes NNS NOUN
    5213 of IN ADP
    5214 the DT DET
    5215 past NN NOUN
    5216 . . PUNCT
    5217 We PRP PRON
    5218 have VBP AUX
    5219 seen VBN VERB
    5220 the DT DET
    5221 war NN NOUN
    5222 and CC CCONJ
    5223 the DT DET
    5224 destruction NN NOUN
    5225 that WDT DET
    5226 have VBP AUX
    5227 ravaged VBN VERB
    5228 and CC CCONJ
    5229 raged VBD VERB
    5230 throughout IN ADP
    5231 the DT DET
    5232 world NN NOUN
    5233 — : PUNCT
    5234 all RB ADV
    5235 across IN ADP
    5236 the DT DET
    5237 world NN NOUN
    5238 . . PUNCT
    5239 The DT DET
    5240 only JJ ADJ
    5241 long JJ ADJ
    5242 - HYPH PUNCT
    5243 term NN NOUN
    5244 solution NN NOUN
    5245 for IN ADP
    5246 these DT DET
    5247 humanitarian JJ ADJ
    5248 disasters NNS NOUN
    5249 , , PUNCT
    5250 in IN ADP
    5251 many JJ ADJ
    5252 cases NNS NOUN
    5253 , , PUNCT
    5254 is VBZ AUX
    5255 to TO PART
    5256 create VB VERB
    5257 the DT DET
    5258 conditions NNS NOUN
    5259 where WRB ADV
    5260 displaced VBN VERB
    5261 persons NNS NOUN
    5262 can MD AUX
    5263 safely RB ADV
    5264 return VB VERB
    5265 home RB ADV
    5266 and CC CCONJ
    5267 begin VB VERB
    5268 the DT DET
    5269 long JJ ADJ
    5270 , , PUNCT
    5271 long JJ ADJ
    5272 process NN NOUN
    5273 of IN ADP
    5274 rebuilding NN NOUN
    5275 . . PUNCT
    5276

     _SP SPACE
    5277 America NNP PROPN
    5278 is VBZ AUX
    5279 willing JJ ADJ
    5280 to TO PART
    5281 find VB VERB
    5282 new JJ ADJ
    5283 friends NNS NOUN
    5284 and CC CCONJ
    5285 to TO PART
    5286 forge VB VERB
    5287 new JJ ADJ
    5288 partnerships NNS NOUN
    5289 where WRB ADV
    5290 shared VBN VERB
    5291 interests NNS NOUN
    5292 align NN NOUN
    5293 . . PUNCT
    5294 We PRP PRON
    5295 want VBP VERB
    5296 harmony NN NOUN
    5297 and CC CCONJ
    5298 stability NN NOUN
    5299 , , PUNCT
    5300 not RB PART
    5301 war NN NOUN
    5302 and CC CCONJ
    5303 conflict NN NOUN
    5304 . . PUNCT
    5305 We PRP PRON
    5306 want VBP VERB
    5307 peace NN NOUN
    5308 , , PUNCT
    5309 wherever WRB ADV
    5310 peace NN NOUN
    5311 can MD AUX
    5312 be VB AUX
    5313 found VBN VERB
    5314 . . PUNCT
    5315

     _SP SPACE
    5316 America NNP PROPN
    5317 is VBZ AUX
    5318 friends NNS NOUN
    5319 today NN NOUN
    5320 with IN ADP
    5321 former JJ ADJ
    5322 enemies NNS NOUN
    5323 . . PUNCT
    5324 Some DT DET
    5325 of IN ADP
    5326 our PRP$ PRON
    5327 closest JJS ADJ
    5328 allies NNS NOUN
    5329 , , PUNCT
    5330 decades NNS NOUN
    5331 ago RB ADV
    5332 , , PUNCT
    5333 fought VBD VERB
    5334 on IN ADP
    5335 the DT DET
    5336 opposite JJ ADJ
    5337 side NN NOUN
    5338 of IN ADP
    5339 these DT DET
    5340 terrible JJ ADJ
    5341 , , PUNCT
    5342 terrible JJ ADJ
    5343 wars NNS NOUN
    5344 . . PUNCT
    5345 This DT DET
    5346 history NN NOUN
    5347 should MD AUX
    5348 give VB VERB
    5349 us PRP PRON
    5350 all DT DET
    5351 faith NN NOUN
    5352 in IN ADP
    5353 the DT DET
    5354 possibilities NNS NOUN
    5355 for IN ADP
    5356 a DT DET
    5357 better JJR ADJ
    5358 world NN NOUN
    5359 . . PUNCT
    5360 Hopefully RB ADV
    5361 , , PUNCT
    5362 the DT DET
    5363 250th JJ ADJ
    5364 year NN NOUN
    5365 for IN ADP
    5366 America NNP PROPN
    5367 will MD AUX
    5368 see VB VERB
    5369 a DT DET
    5370 world NN NOUN
    5371 that WDT DET
    5372 is VBZ VERB
    5373 more RBR ADV
    5374 peaceful JJ ADJ
    5375 , , PUNCT
    5376 more RBR ADV
    5377 just RB ADV
    5378 , , PUNCT
    5379 and CC CCONJ
    5380 more RBR ADV
    5381 free JJ ADJ
    5382 . . PUNCT
    5383

     _SP SPACE
    5384 On IN ADP
    5385 our PRP$ PRON
    5386 100th JJ ADJ
    5387 anniversary NN NOUN
    5388 , , PUNCT
    5389 in IN ADP
    5390 1876 CD NUM
    5391 , , PUNCT
    5392 citizens NNS NOUN
    5393 from IN ADP
    5394 across IN ADP
    5395 our PRP$ PRON
    5396 Nation NN NOUN
    5397 came VBD VERB
    5398 to IN ADP
    5399 Philadelphia NNP PROPN
    5400 to TO PART
    5401 celebrate VB VERB
    5402 America NNP PROPN
    5403 's POS PART
    5404 centennial NN NOUN
    5405 . . PUNCT
    5406 At IN ADP
    5407 that DT DET
    5408 celebration NN NOUN
    5409 , , PUNCT
    5410 the DT DET
    5411 country NN NOUN
    5412 's POS PART
    5413 builders NNS NOUN
    5414 and CC CCONJ
    5415 artists NNS NOUN
    5416 and CC CCONJ
    5417 inventors NNS NOUN
    5418 showed VBD VERB
    5419 off RP ADP
    5420 their PRP$ PRON
    5421 wonderful JJ ADJ
    5422 creations NNS NOUN
    5423 . . PUNCT
    5424 Alexander NNP PROPN
    5425 Graham NNP PROPN
    5426 Bell NNP PROPN
    5427 displayed VBD VERB
    5428 his PRP$ PRON
    5429 telephone NN NOUN
    5430 for IN ADP
    5431 the DT DET
    5432 first JJ ADJ
    5433 time NN NOUN
    5434 . . PUNCT
    5435 Remington NNP PROPN
    5436 unveiled VBD VERB
    5437 the DT DET
    5438 first JJ ADJ
    5439 typewriter NN NOUN
    5440 . . PUNCT
    5441 An DT DET
    5442 early JJ ADJ
    5443 attempt NN NOUN
    5444 was VBD AUX
    5445 made VBN VERB
    5446 at IN ADP
    5447 electric JJ ADJ
    5448 light NN NOUN
    5449 . . PUNCT
    5450 Thomas NNP PROPN
    5451 Edison NNP PROPN
    5452 showed VBD VERB
    5453 an DT DET
    5454 automatic JJ ADJ
    5455 telegraph NN NOUN
    5456 and CC CCONJ
    5457 an DT DET
    5458 electric JJ ADJ
    5459 pen NN NOUN
    5460 . . PUNCT
    5461 Imagine VB VERB
    5462 the DT DET
    5463 wonders NNS NOUN
    5464 our PRP$ PRON
    5465 country NN NOUN
    5466 could MD AUX
    5467 know VB VERB
    5468 in IN ADP
    5469 America NNP PROPN
    5470 's POS PART
    5471 250th JJ ADJ
    5472 year NN NOUN
    5473 . . PUNCT
    5474 Think VB VERB
    5475 of IN ADP
    5476 the DT DET
    5477 marvels NNS NOUN
    5478 we PRP PRON
    5479 can MD AUX
    5480 achieve VB VERB
    5481 if IN SCONJ
    5482 we PRP PRON
    5483 simply RB ADV
    5484 set VBD VERB
    5485 free JJ ADJ
    5486 the DT DET
    5487 dreams NNS NOUN
    5488 of IN ADP
    5489 our PRP$ PRON
    5490 people NNS NOUN
    5491 . . PUNCT
    5492 Cures NNS NOUN
    5493 to IN ADP
    5494 the DT DET
    5495 illnesses NNS NOUN
    5496 that WDT DET
    5497 have VBP AUX
    5498 always RB ADV
    5499 plagued VBN VERB
    5500 us PRP PRON
    5501 are VBP AUX
    5502 not RB PART
    5503 too RB ADV
    5504 much JJ ADJ
    5505 to TO PART
    5506 hope VB VERB
    5507 . . PUNCT
    5508 American JJ ADJ
    5509 footprints NNS NOUN
    5510 on IN ADP
    5511 distant JJ ADJ
    5512 worlds NNS NOUN
    5513 are VBP AUX
    5514 not RB PART
    5515 too RB ADV
    5516 big JJ ADJ
    5517 a DT DET
    5518 dream NN NOUN
    5519 . . PUNCT
    5520 Millions NNS NOUN
    5521 lifted VBD VERB
    5522 from IN ADP
    5523 welfare NN NOUN
    5524 to IN ADP
    5525 work NN NOUN
    5526 is VBZ VERB
    5527 not RB PART
    5528 too RB ADV
    5529 much JJ ADJ
    5530 to TO PART
    5531 expect VB VERB
    5532 . . PUNCT
    5533 And CC CCONJ
    5534 streets NNS NOUN
    5535 where WRB ADV
    5536 mothers NNS NOUN
    5537 are VBP VERB
    5538 safe JJ ADJ
    5539 from IN ADP
    5540 fear NN NOUN
    5541 , , PUNCT
    5542 schools NNS NOUN
    5543 where WRB ADV
    5544 children NNS NOUN
    5545 learn VBP VERB
    5546 in IN ADP
    5547 peace NN NOUN
    5548 , , PUNCT
    5549 and CC CCONJ
    5550 jobs NNS NOUN
    5551 where WRB ADV
    5552 Americans NNPS PROPN
    5553 prosper VBP VERB
    5554 and CC CCONJ
    5555 grow VB VERB
    5556 are VBP AUX
    5557 not RB PART
    5558 too RB ADV
    5559 much JJ ADJ
    5560 to TO PART
    5561 ask VB VERB
    5562 . . PUNCT
    5563

     _SP SPACE
    5564 When WRB ADV
    5565 we PRP PRON
    5566 have VBP VERB
    5567 all DT DET
    5568 of IN ADP
    5569 this DT DET
    5570 , , PUNCT
    5571 we PRP PRON
    5572 will MD AUX
    5573 have VB AUX
    5574 made VBN VERB
    5575 America NNP PROPN
    5576 greater JJR ADJ
    5577 than IN SCONJ
    5578 ever RB ADV
    5579 before RB ADV
    5580 — : PUNCT
    5581 for IN ADP
    5582 all DT DET
    5583 Americans NNPS PROPN
    5584 . . PUNCT
    5585 This DT DET
    5586 is VBZ AUX
    5587 our PRP$ PRON
    5588 vision NN NOUN
    5589 . . PUNCT
    5590 This DT DET
    5591 is VBZ AUX
    5592 our PRP$ PRON
    5593 mission NN NOUN
    5594 . . PUNCT
    5595 But CC CCONJ
    5596 we PRP PRON
    5597 can MD AUX
    5598 only RB ADV
    5599 get VB VERB
    5600 there RB ADV
    5601 together RB ADV
    5602 . . PUNCT
    5603 We PRP PRON
    5604 are VBP AUX
    5605 one CD NUM
    5606 people NNS NOUN
    5607 with IN ADP
    5608 one CD NUM
    5609 destiny NN NOUN
    5610 . . PUNCT
    5611 We PRP PRON
    5612 all DT DET
    5613 bleed VBP VERB
    5614 the DT DET
    5615 same JJ ADJ
    5616 blood NN NOUN
    5617 . . PUNCT
    5618 We PRP PRON
    5619 all DT DET
    5620 salute VBP VERB
    5621 the DT DET
    5622 same JJ ADJ
    5623 great JJ ADJ
    5624 American JJ ADJ
    5625 flag NN NOUN
    5626 . . PUNCT
    5627 And CC CCONJ
    5628 we PRP PRON
    5629 all DT DET
    5630 are VBP AUX
    5631 made VBN VERB
    5632 by IN ADP
    5633 the DT DET
    5634 same JJ ADJ
    5635 God NNP PROPN
    5636 . . PUNCT
    5637

     _SP SPACE
    5638 When WRB ADV
    5639 we PRP PRON
    5640 fulfill VBP VERB
    5641 this DT DET
    5642 vision NN NOUN
    5643 , , PUNCT
    5644 when WRB ADV
    5645 we PRP PRON
    5646 celebrate VBP VERB
    5647 our PRP$ PRON
    5648 250 CD NUM
    5649 years NNS NOUN
    5650 of IN ADP
    5651 glorious JJ ADJ
    5652 freedom NN NOUN
    5653 , , PUNCT
    5654 we PRP PRON
    5655 will MD AUX
    5656 look VB VERB
    5657 back RB ADV
    5658 on RB ADV
    5659 tonight NN NOUN
    5660 as IN ADP
    5661 when WRB ADV
    5662 this DT DET
    5663 new JJ ADJ
    5664 chapter NN NOUN
    5665 of IN ADP
    5666 American JJ ADJ
    5667 greatness NN NOUN
    5668 began VBD VERB
    5669 . . PUNCT
    5670 The DT DET
    5671 time NN NOUN
    5672 for IN ADP
    5673 small JJ ADJ
    5674 thinking NN NOUN
    5675 is VBZ AUX
    5676 over RB ADV
    5677 . . PUNCT
    5678 The DT DET
    5679 time NN NOUN
    5680 for IN ADP
    5681 trivial JJ ADJ
    5682 fights NNS NOUN
    5683 is VBZ AUX
    5684 behind IN ADP
    5685 us PRP PRON
    5686 . . PUNCT
    5687 We PRP PRON
    5688 just RB ADV
    5689 need VBP VERB
    5690 the DT DET
    5691 courage NN NOUN
    5692 to TO PART
    5693 share VB VERB
    5694 the DT DET
    5695 dreams NNS NOUN
    5696 that WDT DET
    5697 fill VBP VERB
    5698 our PRP$ PRON
    5699 hearts NNS NOUN
    5700 , , PUNCT
    5701 the DT DET
    5702 bravery NN NOUN
    5703 to TO PART
    5704 express VB VERB
    5705 the DT DET
    5706 hopes NNS NOUN
    5707 that WDT DET
    5708 stir VBP VERB
    5709 our PRP$ PRON
    5710 souls NNS NOUN
    5711 , , PUNCT
    5712 and CC CCONJ
    5713 the DT DET
    5714 confidence NN NOUN
    5715 to TO PART
    5716 turn VB VERB
    5717 those DT DET
    5718 hopes NNS NOUN
    5719 and CC CCONJ
    5720 those DT DET
    5721 dreams NNS NOUN
    5722 into IN ADP
    5723 action NN NOUN
    5724 . . PUNCT
    5725

     _SP SPACE
    5726 From IN ADP
    5727 now RB ADV
    5728 on RB ADV
    5729 , , PUNCT
    5730 America NNP PROPN
    5731 will MD AUX
    5732 be VB AUX
    5733 empowered VBN VERB
    5734 by IN ADP
    5735 our PRP$ PRON
    5736 aspirations NNS NOUN
    5737 , , PUNCT
    5738 not RB PART
    5739 burdened VBN VERB
    5740 by IN ADP
    5741 our PRP$ PRON
    5742 fears NNS NOUN
    5743 ; , PUNCT
    5744 inspired VBN VERB
    5745 by IN ADP
    5746 the DT DET
    5747 future NN NOUN
    5748 , , PUNCT
    5749 not RB PART
    5750 bound VBN VERB
    5751 by IN ADP
    5752 failures NNS NOUN
    5753 of IN ADP
    5754 the DT DET
    5755 past NN NOUN
    5756 ; : PUNCT
    5757 and CC CCONJ
    5758 guided VBN VERB
    5759 by IN ADP
    5760 our PRP$ PRON
    5761 vision NN NOUN
    5762 , , PUNCT
    5763 not RB PART
    5764 blinded VBN VERB
    5765 by IN ADP
    5766 our PRP$ PRON
    5767 doubts NNS NOUN
    5768 . . PUNCT
    5769

     _SP SPACE
    5770 I PRP PRON
    5771 am VBP AUX
    5772 asking VBG VERB
    5773 all DT DET
    5774 citizens NNS NOUN
    5775 to TO PART
    5776 embrace VB VERB
    5777 this DT DET
    5778 renewal NN NOUN
    5779 of IN ADP
    5780 the DT DET
    5781 American JJ ADJ
    5782 spirit NN NOUN
    5783 . . PUNCT
    5784 I PRP PRON
    5785 am VBP AUX
    5786 asking VBG VERB
    5787 all DT DET
    5788 Members NNS NOUN
    5789 of IN ADP
    5790 Congress NNP PROPN
    5791 to TO PART
    5792 join VB VERB
    5793 me PRP PRON
    5794 in IN ADP
    5795 dreaming VBG VERB
    5796 big JJ ADJ
    5797 and CC CCONJ
    5798 bold JJ ADJ
    5799 , , PUNCT
    5800 and CC CCONJ
    5801 daring VBG VERB
    5802 things NNS NOUN
    5803 for IN ADP
    5804 our PRP$ PRON
    5805 country NN NOUN
    5806 . . PUNCT
    5807 I PRP PRON
    5808 am VBP AUX
    5809 asking VBG VERB
    5810 everyone NN PRON
    5811 watching VBG VERB
    5812 tonight NN NOUN
    5813 to TO PART
    5814 seize VB VERB
    5815 this DT DET
    5816 moment NN NOUN
    5817 . . PUNCT
    5818 Believe VB VERB
    5819 in IN ADP
    5820 yourselves NNS NOUN
    5821 , , PUNCT
    5822 believe VB VERB
    5823 in IN ADP
    5824 your PRP$ PRON
    5825 future NN NOUN
    5826 , , PUNCT
    5827 and CC CCONJ
    5828 believe VB VERB
    5829 , , PUNCT
    5830 once RB ADV
    5831 more JJR ADJ
    5832 , , PUNCT
    5833 in IN ADP
    5834 America NNP PROPN
    5835 . . PUNCT
    5836

     _SP SPACE
    5837 Thank VBP VERB
    5838 you PRP PRON
    5839 , , PUNCT
    5840 God NNP PROPN
    5841 bless VBP VERB
    5842 you PRP PRON
    5843 , , PUNCT
    5844 and CC CCONJ
    5845 God NNP PROPN
    5846 bless VBP VERB
    5847 the DT DET
    5848 United NNP PROPN
    5849 States NNP PROPN
    5850 . . PUNCT

### Noun chunks

Chunking is a process of getting just specific part of speeches. The most popular is the noun chunking. It allow us to get the general meaning of what is the text about.

```python
for np in doc.noun_chunks:
    print(np)
```

    you
    Mr. Vice President
    Members
    Congress
    the First Lady
    the United States
    citizens
    America
    Tonight
    we
    the conclusion
    our celebration
    Black History Month
    we
    our Nation's path
    civil rights
    the work
    Recent threats
    Jewish community centers
    vandalism
    Jewish cemeteries
    last week's shooting
    Kansas City
    us
    we
    a nation
    policies
    we
    a country
    hate
    evil
    its very ugly forms
    Each American generation
    the torch
    truth
    liberty
    justice
    an unbroken chain
    the present
    That torch
    our hands
    we
    it
    the world
    I
    a message
    unity
    strength
    it
    a message
    my heart
    A new chapter
    American greatness
    A new national pride
    our Nation
    a new surge
    optimism
    impossible dreams
    our grasp
    What
    we
    the renewal
    the American spirit
    Our allies
    America
    All the nations
    the world
    friend
    foe
    America
    America
    America
    9 years
    the United States
    the 250th anniversary
    our founding
    the day
    we
    our independence
    It
    the great milestones
    the history
    the world
    what
    America
    we
    our 250th year
    What kind
    country
    we
    our children
    I
    the mistakes
    recent decades
    the course
    our future
    we
    our middle class shrink
    we
    our jobs
    wealth
    foreign countries
    We
    one global project
    the fates
    our children
    the inner cities
    Chicago
    Baltimore
    Detroit
    so many other places
    our land
    We
    the borders
    other nations
    our own borders
    anyone
    drugs
    a now unprecedented rate
    we
    trillions
    trillions
    dollars
    our infrastructure
    home
    the Earth
    our feet
    The rebellion
    a quiet protest
    families
    all colors
    creeds
    families
    who
    a fair shot
    their children
    a fair hearing
    their concerns
    the quiet voices
    a loud chorus
    thousands
    citizens
    cities
    our country
    the chorus
    an earthquake
    the people
    the tens
    millions
    they
    crucial demand
    America
    its own citizens
    we
    America
    industries
    life
    Heroic veterans
    the care
    they
    Our military
    the resources
    its brave warriors
    Crumbling infrastructure
    new roads
    bridges
    tunnels
    airports
    our very, very beautiful land
    Our terrible drug epidemic
    our neglected inner cities
    a rebirth
    hope
    safety
    opportunity
    we
    our promises
    the American people
    you
    It
    over a month
    my Inauguration
    I
    this moment
    the Nation
    the progress
    I
    those promises
    my election
    Ford
    Fiat Chrysler
    General Motors
    Sprint
    Softbank
    Lockheed
    Intel
    Walmart
    many others
    they
    billions
    billions
    dollars
    the United States
    tens of thousands
    new American jobs
    The stock market
    value
    the election
    November
    a record
    We
    taxpayers
    hundreds of millions
    dollars
    the price
    fantastic
    it
    a fantastic—new F-35 jet fighter
    we
    billions
    contracts
    our Government
    We
    a hiring freeze
    nonmilitary and nonessential Federal workers
    We
    the swamp
    government corruption
    a 5-year ban
    lobbying
    executive branch officials
    a lifetime ban—[applause]—thank
    you
    you
    And a lifetime ban
    lobbyists
    a foreign government
    We
    a historic effort
    job-crushing regulations
    a deregulation
    Task Force
    every Government agency
    we
    a new rule
    every one new regulation
    two old regulations
    We
    the regulations
    the future
    livelihood
    our great coal miners
    We
    the way
    the construction
    the Keystone
    Dakota Access pipelines
    tens of thousands
    jobs
    I
    a new directive
    new American pipelines
    American steel
    We
    the United States
    the job-killing Trans-Pacific Partnership
    the help
    Prime Minister Justin Trudeau
    we
    a council
    our neighbors
    Canada
    women entrepreneurs
    access
    the networks
    markets
    capital
    they
    a business
    their financial dreams
    our citizens
    I
    the Department
    Justice
    a Task Force
    Violent Crime
    I
    the Departments
    Homeland Security
    Justice
    the Department
    State
    the Director
    National Intelligence
    an aggressive strategy
    the criminal cartels
    our Nation
    We
    the drugs
    our country
    our youth
    we
    treatment
    who
    the same time
    my administration
    the pleas
    the American people
    immigration enforcement
    border security
    our immigration laws
    we
    wages
    billions
    billions
    dollars
    our communities
    everyone
    We
    all Americans
    an environment
    lawless chaos
    We
    integrity
    the rule
    law
    our borders
    that reason
    we
    the construction
    a great, great wall
    our southern border
    we
    we
    gang members
    drug dealers
    criminals
    our communities
    prey
    our very innocent citizens
    Bad ones
    I
    I
    the campaign
    Congress
    who
    we
    our laws
    I
    you
    this one question
    What
    you
    the American family
    their jobs
    their income
    their loved one
    America
    its laws
    its borders
    Our obligation
    the citizens
    the United States
    We
    strong measures
    our Nation
    radical Islamic terrorism
    data
    the Department
    Justice
    individuals
    terrorism
    terrorism-related offenses
    our country
    We
    the attacks
    home
    Boston
    San Bernardino
    the Pentagon
    We
    the attacks
    France
    Belgium
    Germany
    the world
    It
    uncontrolled entry
    places
    proper vetting
    the high honor
    admission
    the United States
    this country
    its people
    its values
    We
    a beachhead
    terrorism
    America
    We
    our Nation
    a sanctuary
    extremists
    my administration
    improved vetting procedures
    we
    new steps
    our Nation
    who
    us
    I
    the Department
    Defense
    a plan
    ISIS
    a network
    lawless savages
    Muslims
    Christians
    men
    women
    children
    all faiths
    all beliefs
    We
    our allies
    our friends
    allies
    the Muslim world
    this vile enemy
    our planet
    I
    new sanctions
    entities
    individuals
    who
    Iran's ballistic missile program
    our unbreakable alliance
    the State
    Israel
    I
    my promise
    a Justice
    the United States Supreme Court
    my list
    20 judges
    who
    our Constitution
    I
    Maureen Scalia
    us
    the gallery
    you
    Her late, great husband
    Antonin Scalia
    a symbol
    American justice
    his seat
    we
    Judge Neil Gorsuch
    a man
    incredible skill
    deep devotion
    the law
    He
    the Court
    Appeals
    I
    the Senate
    his nomination
    I
    the next steps
    we
    a country
    we
    the circumstances
    we
    Ninety-four million Americans
    the labor force
    Over 43 million people
    poverty
    over 43 million Americans
    food stamps
    5 people
    their prime working years
    We
    the worst financial recovery
    65 years
    the last 8 years
    the past administration
    more new debt
    the other Presidents
    We
    more than one-fourth
    our manufacturing jobs
    NAFTA
    we
    60,000 factories
    China
    the World Trade Organization
    Our trade deficit
    goods
    the world
    nearly $800 billion dollars
    we
    a series
    tragic foreign policy disasters
    us
    the differences
    party
    It
    us
    the American spirit
    every challenge
    history
    our goals
    home
    we
    the engine
    the American economy
    it
    companies
    business
    the United States
    companies
    our country
    American companies
    the highest rates
    the world
    My economic team
    historic tax reform
    the tax rate
    our companies
    they
    anyone
    It
    a big, big cut
    the same time
    we
    massive tax relief
    the middle class
    We
    a level playing field
    American companies
    our workers
    it
    we
    products
    America
    many other countries
    us
    very high tariffs
    taxes
    foreign companies
    their products
    America
    we
    them
    nothing
    almost nothing
    I
    officials
    workers
    a great American company
    Harley-Davidson
    fact
    they
    their magnificent motorcycles
    the U.S.A.
    the front lawn
    the White House
    they
    me
    I
    you
    our meeting
    I
    them
    you
    business
    They
    it
    I
    them
    you
    other countries
    mainly international sales
    They
    me
    they
    they
    it
    it
    business
    other countries
    they
    our goods
    such a high rate
    They
    the case
    another country
    they
    their motorcycles
    100 percent
    They
    a change
    I
    I
    free trade
    it
    fair trade
    It
    a long time
    we
    fair trade
    The first Republican President
    Abraham Lincoln
    the "abandonment
    the protective policy
    the American Government
    our people
    Lincoln
    it
    time
    we
    his advice
    his words
    I
    America
    its great companies
    workers
    advantage
    us
    They
    advantage
    our country
    I
    millions
    jobs
    our workers
    our system
    legal immigration
    The current, outdated system
    wages
    our poorest workers
    great pressure
    taxpayers
    Nations
    the world
    Canada
    Australia
    many others
    a merit-based immigration system
    It
    a basic principle
    a country
    themselves
    America
    we
    this rule
    the very public resources
    our poorest citizens
    the National Academy
    Sciences
    our current immigration system
    American taxpayers
    many billions
    dollars
    this current system
    lower skilled immigration
    a merit-based system
    we
    so many more benefits
    It
    countless dollars
    workers' wages
    families
    immigrant families
    the middle class
    they
    it
    they
    I
    real and positive immigration reform
    we
    the following goals
    jobs
    wages
    Americans
    our Nation's security
    respect
    our laws
    we
    the wellbeing
    American citizens
    I
    Republicans
    Democrats
    an outcome
    our country
    decades
    Another Republican President
    Dwight D. Eisenhower
    the last truly great national infrastructure program
    the building
    the Interstate Highway System
    The time
    a new program
    national rebuilding
    America
    the Middle East
    our infrastructure
    home
    we
    our country
    maybe even three times
    we
    people
    who
    the ability
    our national rebuilding
    I
    Congress
    legislation
    a $1 trillion investment
    infrastructure
    the United States
    both public and private capital
    millions
    new jobs
    This effort
    two core principles
    I
    this Congress
    Obamacare
    reforms
    choice
    access
    lower costs
    the same time
    better health care
    every American
    Government-approved health insurance
    the right solution
    our country
    The way
    health insurance
    everyone
    the cost
    health insurance
    what
    we
    premiums
    double and triple digits
    an example
    Arizona
    Governor Matt Bevin
    Kentucky
    Obamacare
    his State
    the State
    Kentucky
    it
    One-third
    the counties
    only one insurer
    they
    them
    They
    them
    They
    many Americans
    no choice
    no choice
    you
    you
    your doctor
    your plan
    We
    those promises
    Obamacare
    we
    all Americans
    Action
    a choice
    it
    a necessity
    I
    all Democrats
    Republicans
    Congress
    us
    Americans
    this imploding Obamacare disaster
    the principles
    the Congress
    we
    a better health care system
    all Americans
    we
    Americans
    preexisting conditions
    access
    coverage
    we
    a stable transition
    Americans
    the health care exchanges
    we
    Americans
    their own coverage
    the use
    tax credits
    health savings accounts
    it
    the plan
    they
    the plan
    them
    our Government
    we
    our State Governors
    the resources
    flexibility
    they
    Medicaid
    no one
    we
    legal reforms
    patients
    doctors
    unnecessary costs
    the price
    insurance
    work
    the artificially high price
    drugs
    them
    the time
    Americans
    the freedom
    health insurance
    State lines
    a truly competitive national marketplace
    costs
    far better care
    Everything
    our country
    Every problem
    every hurting family
    healing
    hope
    Our citizens
    forces
    the job
    it
    so many other things
    Democrats
    Republicans
    the good
    our country
    the good
    the American people
    My administration
    members
    both parties
    childcare
    new parents
    they
    women's health
    clean air
    clean water
    our military
    our infrastructure
    True love
    our people
    us
    common ground
    the common good
    behalf
    every American child
    who
    a much brighter future
    An incredible young woman
    us
    who
    an inspiration
    us
    Today
    Rare Disease Day
    us
    the gallery
    a rare disease survivor
    Megan Crowley
    Megan
    Pompe disease
    a rare and serious illness
    she
    She
    this news
    Megan's dad
    John
    everything
    he
    the life
    his precious child
    He
    a company
    a cure
    the drug
    Megan's life
    she
    a sophomore
    Notre Dame
    Megan's story
    the unbounded power
    a father's love
    a daughter
    our slow and burdensome approval process
    the Food and Drug Administration
    too many advances
    the one
    Megan's life
    need
    we
    the restraints
    the FDA
    our Government
    we
    far more miracles
    Megan
    fact
    our children
    a nation
    miracles
    this future
    we
    the mind
    the souls
    every American child
    Education
    the civil rights issue
    our time
    I
    members
    both parties
    an education bill
    school choice
    disadvantaged youth
    millions
    African American and Latino children
    These families
    charter
    magnet
    home school
    them
    us
    the gallery
    a remarkable woman
    Denisha Merriweather
    a young girl
    Denisha
    school
    third grade
    she
    a private center
    learning
    great learning center
    the help
    a tax credit
    a scholarship program
    she
    her family
    high school
    college
    she
    her master's degree
    social work
    We
    all children
    the cycle
    poverty
    Denisha
    the cycle
    poverty
    we
    the cycle
    violence
    The murder rate
    its largest single-year increase
    nearly half a century
    Chicago
    more than 4,000 people
    the murder rate
    our society
    Every American child
    a safe community
    a great school
    access
    a high-paying job
    this future
    we
    the men
    women
    law enforcement
    We
    bridges
    cooperation
    trust
    the wedge
    disunity
    it
    what
    it
    division
    It
    pure, unadulterated division
    We
    Police
    sheriffs
    members
    our community
    They
    friends
    neighbors
    they
    mothers
    fathers
    sons
    daughters
    they
    loved ones
    who
    they
    We
    the incredible men
    women
    law enforcement
    we
    the victims
    crime
    I
    the Department
    Homeland Security
    an office
    American victims
    The office
    VOICE
    Victims
    Immigration Crime Engagement
    We
    a voice
    who
    our media
    special interests
    us
    the audience
    four very brave Americans
    whose Government
    them
    Their names
    Jamiel Shaw
    Susan Oliver
    Jenna Oliver
    Jessica Davis
    Jamiel's 17-year-old son
    an illegal immigrant gang member
    who
    prison
    Jamiel Shaw, Jr.
    an incredible young man
    unlimited potential
    who
    college
    he
    a great college quarterback
    he
    the chance
    His father
    who
    the audience
    a very good friend
    mine
    you
    you
    us
    Susan Oliver
    Jessica Davis
    Deputy Sheriff Danny Oliver
    Detective Michael Davis
    the line
    duty
    California
    They
    pillars
    their community
    These brave men
    an illegal immigrant
    a criminal record
    two prior deportations
    our country
    Susan
    her daughter
    Jenna
    I
    you
    your father
    a hero
    you
    the love
    an entire country
    you
    you
    Jamiel
    Jenna
    Susan
    Jessica
    I
    you
    we
    justice
    Your loved ones
    We
    their memory
    America
    we
    the men
    women
    the United States military
    the tools
    they
    war
    they
    they
    they
    I
    Congress
    a budget
    the military
    the defense sequester
    the largest increases
    national defense spending
    American history
    My budget
    funding
    our veterans
    Our veterans
    this Nation
    we
    them
    The challenges
    we
    a nation
    our people
    none
    who
    America
    uniform
    We
    Carryn Owens
    the widow
    U.S. Navy Special Operator
    Senior Chief William "Ryan" Owens
    Ryan
    he
    a warrior
    a hero
    terrorism
    our Nation
    I
    our great General Mattis
    who
    I
    a part
    a highly successful raid
    large amounts
    vital intelligence
    many more victories
    the future
    our enemy
    Ryan's legacy
    eternity
    you
    Ryan
    you
    he
    I
    he
    a record
    the Bible
    us
    no greater act
    love
    one's life
    one's friends
    Ryan
    his life
    his friends
    his country
    our freedom
    we
    Ryan
    those allies
    who
    what kind
    a friend
    America
    the heroes
    who
    our uniform
    Our foreign policy
    a direct, robust, and meaningful engagement
    the world
    It
    American leadership
    vital security interests
    we
    our allies
    the globe
    We
    NATO
    an alliance
    the bonds
    two world wars
    fascism
    a cold war
    communism
    our partners
    their financial obligations
    our very strong and frank discussions
    they
    fact
    I
    you
    the money
    We
    our partners
    NATO
    the Middle East
    the Pacific
    a direct and meaningful role
    both strategic and military operations
    their fair share
    the cost
    We
    historic institutions
    we
    the foreign rights
    all nations
    they
    our rights
    a nation
    Free nations
    the best vehicle
    the will
    the people
    America
    the right
    all nations
    their own path
    My job
    the world
    My job
    the United States
    America
    we
    America
    less conflict
    We
    the mistakes
    the past
    We
    the war
    the destruction
    the world
    the world
    The only long-term solution
    these humanitarian disasters
    many cases
    the conditions
    displaced persons
    the long, long process
    rebuilding
    America
    new friends
    new partnerships
    shared interests
    We
    harmony
    stability
    not war
    conflict
    We
    peace
    peace
    America
    friends
    former enemies
    our closest allies
    the opposite side
    these terrible, terrible wars
    This history
    us
    all faith
    the possibilities
    a better world
    the 250th year
    America
    a world
    our 100th anniversary
    citizens
    our Nation
    Philadelphia
    America's centennial
    that celebration
    the country's builders
    artists
    inventors
    their wonderful creations
    Alexander Graham Bell
    his telephone
    the first time
    Remington
    the first typewriter
    An early attempt
    electric light
    Thomas Edison
    an automatic telegraph
    an electric pen
    the wonders
    our country
    America's 250th year
    the marvels
    we
    we
    the dreams
    our people
    Cures
    the illnesses
    us
    American footprints
    distant worlds
    too big a dream
    Millions
    welfare
    work
    mothers
    fear
    children
    peace
    Americans
    we
    we
    America
    all Americans
    our vision
    our mission
    we
    We
    one people
    one destiny
    We
    the same blood
    We
    the same great American flag
    we
    the same God
    we
    this vision
    we
    our 250 years
    glorious freedom
    we
    this new chapter
    American greatness
    The time
    small thinking
    The time
    trivial fights
    us
    We
    the courage
    the dreams
    our hearts
    the bravery
    the hopes
    our souls
    the confidence
    those hopes
    those dreams
    action
    America
    our aspirations
    our fears
    the future
    failures
    the past
    our vision
    our doubts
    I
    all citizens
    this renewal
    the American spirit
    I
    all Members
    Congress
    me
    things
    our country
    I
    everyone
    this moment
    yourselves
    your future
    America
    you
    God
    you
    God
    the United States

### Named entity recognition

The last feature that we show here is the named entitiy resolution. It returns a NER of each word.

```python
for entity in doc.ents:
    print(entity.label_, entity.text)
```

    PERSON Speaker
    ORG Congress
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    ORG the Department of Justice
    PRODUCT a Task Force
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    MONEY billions and billions of dollars
    NORP Americans
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    ORG Congress
    CARDINAL one
    NORP American
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    NORP Islamic
    ORG the Department of Justice
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    GPE San Bernardino
    ORG Pentagon
    ORG the World Trade Center
    GPE France
    GPE Belgium
    GPE Germany
    GPE the United States
    GPE America
    ORG the Department of Defense
    ORG ISIS
    NORP Muslims
    NORP Christians
    NORP Muslim
    GPE Iran
    GPE the State of Israel
    ORG Justice
    GPE the United States Supreme Court
    CARDINAL 20
    LAW Constitution
    PERSON Maureen Scalia
    TIME tonight
    PERSON Maureen
    PERSON Antonin Scalia
    NORP American
    PERSON Neil Gorsuch
    ORG the Court of Appeals
    ORG Senate
    TIME Tonight
    CARDINAL Ninety-four million
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    CARDINAL Over 43 million
    CARDINAL over 43 million
    NORP Americans
    CARDINAL More than 1
    CARDINAL 5
    DATE 65 years
    DATE the last 8 years
    CARDINAL more than one-fourth
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    CARDINAL one
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### Bag of Words

Many machine learning methods cannot use strings as features, we have to encode it using numbers.

We can easily do this using __Bag Of Words (BOW)__ technique and marvelous __sklearn__ library:

```python
from sklearn.feature_extraction.text import CountVectorizer

vectorizer = CountVectorizer()

corpus = [
     'Bag Of Words is based on counting',
     'words occurences throughout multiple documents.',
     'This is the third document.',
     'As you can see most of the words occur only once.',
     'This gives us a pretty sparse matrix, see below. Really, see below',
]

X = vectorizer.fit_transform(corpus)
print(X.toarray())
```

    [[0 1 1 0 0 1 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0]
     [0 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0]
     [0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0]
     [1 0 0 0 1 0 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 1 0 1 0 0 0 0 1 1]
     [0 0 0 2 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1 2 1 0 0 1 0 1 0 0]]

Each document is represented by the row. Values ranging from 0 to N represent whether and how many times the word occured in the document. You can see what word corresponds to which column by issuing get_feature_names() on vectorizer object.

```python
vectorizer.get_feature_names()
```

    ['as',
     'bag',
     'based',
     'below',
     'can',
     'counting',
     'document',
     'documents',
     'gives',
     'is',
     'matrix',
     'most',
     'multiple',
     'occur',
     'occurences',
     'of',
     'on',
     'once',
     'only',
     'pretty',
     'really',
     'see',
     'sparse',
     'the',
     'third',
     'this',
     'throughout',
     'us',
     'words',
     'you']

This approach allows us to easily describe the whole corpora, but it lacks informations crucial for solving some tasks.

### TF-IDF

Look at word is. It is used in most documents many times, yet it does not tell us anything about them. Let's think about sentiment analysis: if words like great or awesome occur frequently in comparison with another documents it may suggest positive attitude.

TF-IDF is one way to encode this information and I'll walk you through it step by step.

First part of TF-IDF is, yes, you guessed it, TF, which means Term Frequency. It can be calculated as:

\begin{equation}
tf_{ij}=\frac{n_{ij}}{\sum n_{ij}},
\end{equation}
where $n_{ij}$ is the number of occurence of word $i$ in document $j$.

```python
import numpy as np

corpus = [
'Tom has cat',
'Tom has fish',
'Tom is polish',
]

def tf(corpus):
    vec = CountVectorizer()
    bow_representation = vec.fit_transform(corpus)
    words_per_corpus = bow_representation.sum(axis=1)
    return np.divide(np.array(bow_representation.toarray()),np.array(words_per_corpus).reshape((5,))[:,None])

```

For each document we count how many times it occurred (BoW implementaion) and divide by the count of all words in this document.

Next part is IDF, which stands for Inverse Document Frequency:

\begin{equation}
idf=\log(\frac{N}{df_{t}}),
\end{equation}
where $N$ is the total number of documents and $df_{t}$ is number of documents containing $t$.

```python
def idf(corpus):
    document_count = len(corpus)
    bow_representation = CountVectorizer().fit_transform(corpus)
    return np.log(document_count / np.count_nonzero(bow_representation.toarray(), axis=0))
```

First we calculate number of documents in corpus (number of rows in our case). Next, for each word, we calculate documents containing said word at least once.

Taking logarithm allows us to dampen the effect of idf. For example, the difference between term occuring in 40 out of 50 documents and 45 out of 50 documents will be smaller than difference between 1/50 and 5/50. This puts a bigger emphasis on rarely occuring terms as they are more informative.

Finally, for the whole thing to work, we simply multiply both:

```python
def tf_idf(corpus):
    return tf(corpus) * idf(corpus)
```

Let's calculate it:

```python
corpus = [
     'Bag Of Words is based on counting',
     'words occurences throughout multiple documents.',
     'This is the third document.',
     'As you can see most of the words occur only once.',
     'This gives us a pretty sparse matrix, see below. Really, see below',
]

tfidf_result = tf_idf(corpus)

print(tfidf_result.shape)
```

    (5, 30)

In Jupyter it's easier to display results with pandas:

```python
import pandas as pd
pd.DataFrame(tfidf_result).head()
```

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>0</th>
      <th>1</th>
      <th>2</th>
      <th>3</th>
      <th>4</th>
      <th>5</th>
      <th>6</th>
      <th>7</th>
      <th>8</th>
      <th>9</th>
      <th>...</th>
      <th>20</th>
      <th>21</th>
      <th>22</th>
      <th>23</th>
      <th>24</th>
      <th>25</th>
      <th>26</th>
      <th>27</th>
      <th>28</th>
      <th>29</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>0.000000</td>
      <td>0.22992</td>
      <td>0.22992</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.22992</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.130899</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.072975</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>1</th>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.321888</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.321888</td>
      <td>0.000000</td>
      <td>0.102165</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>2</th>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.321888</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.183258</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.183258</td>
      <td>0.321888</td>
      <td>0.183258</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
    <tr>
      <th>3</th>
      <td>0.146313</td>
      <td>0.00000</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.146313</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>...</td>
      <td>0.000000</td>
      <td>0.083299</td>
      <td>0.000000</td>
      <td>0.083299</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.046439</td>
      <td>0.146313</td>
    </tr>
    <tr>
      <th>4</th>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.00000</td>
      <td>0.292625</td>
      <td>0.000000</td>
      <td>0.00000</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.146313</td>
      <td>0.000000</td>
      <td>...</td>
      <td>0.146313</td>
      <td>0.166598</td>
      <td>0.146313</td>
      <td>0.000000</td>
      <td>0.000000</td>
      <td>0.083299</td>
      <td>0.000000</td>
      <td>0.146313</td>
      <td>0.000000</td>
      <td>0.000000</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 30 columns</p>
</div>

There are many versions of tf-idf, some use different smoothing, use additional logarithm for tf part and so on. Each transforms corpora a little differently, and appropriate should be used based on effect we would like to obtain.

### Summary
This constitutes the first NLP-related part of our course and we have gathered some useful and interesting informations

### References

[1] Natural Language Processing with Python, Edward Loper, Ewan Klein, Steven Bird. O'Reilly 2009

[2] Applied Text Analysis with Python, Tony Ojeda , Rebecca Bilbro , Benjamin Bengfort. O'Reilly 2018

[3] Feature Engineering for Machine Learning, Amanda Casari , Alice Zheng. O'Reilly 2018