214 lines
3.8 KiB
Python
214 lines
3.8 KiB
Python
# Natural Language Toolkit: Some texts for exploration in chapter 1 of the book
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#
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# Copyright (C) 2001-2019 NLTK Project
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# Author: Steven Bird <stevenbird1@gmail.com>
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#
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# URL: <http://nltk.org/>
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# For license information, see LICENSE.TXT
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from nltk.corpus import (
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gutenberg,
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genesis,
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inaugural,
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nps_chat,
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webtext,
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treebank,
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wordnet,
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)
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from nltk.text import Text
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from nltk.probability import FreqDist
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from nltk.util import bigrams
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print("*** Introductory Examples for the NLTK Book ***")
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print("Loading text1, ..., text9 and sent1, ..., sent9")
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print("Type the name of the text or sentence to view it.")
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print("Type: 'texts()' or 'sents()' to list the materials.")
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text1 = Text(gutenberg.words("melville-moby_dick.txt"))
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print("text1:", text1.name)
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text2 = Text(gutenberg.words("austen-sense.txt"))
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print("text2:", text2.name)
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text3 = Text(genesis.words("english-kjv.txt"), name="The Book of Genesis")
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print("text3:", text3.name)
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text4 = Text(inaugural.words(), name="Inaugural Address Corpus")
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print("text4:", text4.name)
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text5 = Text(nps_chat.words(), name="Chat Corpus")
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print("text5:", text5.name)
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text6 = Text(webtext.words("grail.txt"), name="Monty Python and the Holy Grail")
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print("text6:", text6.name)
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text7 = Text(treebank.words(), name="Wall Street Journal")
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print("text7:", text7.name)
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text8 = Text(webtext.words("singles.txt"), name="Personals Corpus")
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print("text8:", text8.name)
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text9 = Text(gutenberg.words("chesterton-thursday.txt"))
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print("text9:", text9.name)
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def texts():
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print("text1:", text1.name)
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print("text2:", text2.name)
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print("text3:", text3.name)
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print("text4:", text4.name)
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print("text5:", text5.name)
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print("text6:", text6.name)
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print("text7:", text7.name)
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print("text8:", text8.name)
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print("text9:", text9.name)
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sent1 = ["Call", "me", "Ishmael", "."]
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sent2 = [
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"The",
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"family",
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"of",
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"Dashwood",
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"had",
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"long",
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"been",
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"settled",
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"in",
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"Sussex",
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".",
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]
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sent3 = [
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"In",
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"the",
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"beginning",
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"God",
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"created",
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"the",
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"heaven",
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"and",
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"the",
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"earth",
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".",
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]
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sent4 = [
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"Fellow",
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"-",
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"Citizens",
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"of",
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"the",
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"Senate",
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"and",
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"of",
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"the",
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"House",
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"of",
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"Representatives",
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":",
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]
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sent5 = [
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"I",
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"have",
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"a",
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"problem",
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"with",
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"people",
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"PMing",
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"me",
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"to",
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"lol",
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"JOIN",
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]
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sent6 = [
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"SCENE",
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"1",
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":",
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"[",
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"wind",
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"]",
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"[",
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"clop",
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"clop",
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"clop",
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"]",
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"KING",
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"ARTHUR",
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":",
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"Whoa",
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"there",
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"!",
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]
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sent7 = [
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"Pierre",
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"Vinken",
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",",
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"61",
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"years",
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"old",
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",",
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"will",
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"join",
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"the",
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"board",
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"as",
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"a",
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"nonexecutive",
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"director",
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"Nov.",
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"29",
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".",
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]
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sent8 = [
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"25",
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"SEXY",
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"MALE",
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",",
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"seeks",
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"attrac",
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"older",
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"single",
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"lady",
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",",
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"for",
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"discreet",
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"encounters",
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".",
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]
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sent9 = [
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"THE",
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"suburb",
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"of",
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"Saffron",
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"Park",
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"lay",
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"on",
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"the",
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"sunset",
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"side",
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"of",
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"London",
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",",
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"as",
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"red",
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"and",
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"ragged",
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"as",
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"a",
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"cloud",
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"of",
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"sunset",
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".",
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]
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def sents():
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print("sent1:", " ".join(sent1))
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print("sent2:", " ".join(sent2))
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print("sent3:", " ".join(sent3))
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print("sent4:", " ".join(sent4))
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print("sent5:", " ".join(sent5))
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print("sent6:", " ".join(sent6))
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print("sent7:", " ".join(sent7))
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print("sent8:", " ".join(sent8))
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print("sent9:", " ".join(sent9))
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