NLP Using Python

Which of the following is not a collocation, associated with text6?Straight table

BIGRAMS appearing in a text

What is the frequency of bigram ('clop','clop') in text collection text6?26

How many trigrams are possible from the sentence Python is cool?4

How many trigrams are possible from the sentence Python is cool!!!?4

Which of the following word occurs frequently after the word FRENCH in text collection text6?GUARD

What is the frequency of bigram ('HEAD','KNIGHT') in text collection text6?29

What is the frequency of bigram ('BLACK','KNIGHT') in text collection text6?32

What is the frequency of bigram ('King','Arthur') in text collection text6?16

Which of the following word occurs frequently after the word Holy in text collection text6?Grail

Which of the following function is used to generate a set of all possible n consecutive words appearing in a text? ngrams()

Which of the following class is used to convert a list of tokens into NLTK text?nltk.Text correct

Which of the following function is used to break given text into sentences? sent_tokenize

sentence = """At eight o'clock on Thursday morning... Arthur didn't feel verygood."""

tokens = nltk.word_tokenize(sentence)

print(tokens)tagged = nltk.pos_tag(tokens)

print(tagged[0:6])

entities = nltk.chunk.ne_chunk(tagged)print(entities) from nltk.corpus import treebankt = treebank.parsed_sents('wsj_0001.mrg')[0]t.draw()

wordfreq = nltk.FreqDist(words)wordfreq.most_common(2)[('programming', 2), ('.', 2)]word nltk.import nl

nltk.download('book')from nltk.book import *.

text1.findall("<tri.*r>")type(text1)

n_unique_words = len(set(text1))

text1_lcw = [ word.lower() for word in set(text1) ]n_unique_words_lc = len(set(text1_lcw))word_coverage1 = n_words / n_unique_wordsword_coverage2 = n_words / n_unique_words_lcbig_words = [word for word in set(text1) if len(word) > 17 ]sun_words = [word for word in set(text1) if word.startswith('Sun') ]text1_freq = nltk.FreqDist(text1)

fdisttop3_text1 = text1_freq.most_common(3)

####TEXT CORPORAPopular Text CorporaGenesis: It is a collection of few words across multiple languages.Brown: It is the first electronic corpus of one million English words.

Other Corpus in nltkGutenberg : Collections from Project GutenbergInaugural : Collection of U.S Presidents inaugural speeches

stopwords : Collection of stop words.reuters : Collection of news articles.cmudict : Collection of CMU Dictionary words.movie_reviews : Collection of Movie Reviews.np_chat : Collection of chat text.names : Collection of names associated with males and females.state_union : Collection of state union address.wordnet : Collection of all lexical entries.

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How many times do the word gas occur in text collections, grouped into genre 'gas'?Consider reuters corpus.10

How many times do the words gasoline and barrels occur in text collections, groupedinto genre gas ? Consider reuters corpus.77,64

How many times do the words tonnes and year occur in text collections, grouped into genre sugar ? Consider reuters corpus.355,196

Which of the following method is used to view the conditions, which are used whilecomputing conditional frequency distributions?conditons()

Which of the following class is used to determine count of all tokens present in agiven text ?FreqDist

lead and smelter40,33

216618.55

['noise','surprise','wise','apologise'] = 4

How many times each unique word of text6 collection is repeated on an average?7.8 times

Count the number of words in text collection, text6, ending with ship?1

How many times does the word 'BROTHER' occur in text collection text6?4

What is the frequency of word 'ARTHUR' in text collection text6?0.0132

Which of the following modules is used for performing Natural language processingin python?nltk

Which of the following expression is used to download all the required corpus andcollections , related to NLTK Book ?nltk.download('book')

What is range of length of words present in text collection text6?1 to 13

What are the categories to which the text collection text/16438, of reuters corpusis tagged to ?crude, nat-gas

In how many number of categories, are all text collections of brown corpus groupedinto?15

Which of the following method is used to determine the number of characters presentin a corpus?char() wrong

Which of the following expression imports genesis corpus into the workingenvironment?form ntlk.corpus import genesis #############items = ['apple', 'apple', 'kiwi', 'cabbage', 'cabbage', 'potato']nltk.FreqDist(items)

How many times do the word sugar occur in text collections, grouped into genre'sugar'? Consider reuters corpus.521

How many times do the word zinc occur in text collections, grouped into genre'zinc'? Consider reuters corpus70

Which of the following class is used to determine count of all tokens present in agiven text ?FreqDist

Which of the following class is used to determine count of all tokens present intext collections, grouped bya specific condition?ConditionalFreqDist

Which of the following method is used, on a conditional frequency distribution, inorder to display frequency of few samples derived under few conditions?tabulate()

What is the number of sentences obtained after breaking 'Python is cool!!!' intosentences using sent_tokenize2

Which of the following method is used to tokenize a text based on a regularexpression?regexp_tokenize()

Which of the following class is used to convert a list of tokens into NLTK text?nltk.Text correct

Which of the following module can be used to read text data from a pdf document?pypdf

Which of the following module is used to download text from a HTML file?urllib

Which of the following is not a collocation, associated with text6?squeak squeak

What is the frequency of bigram ('King', 'Arthur') in text collection text6?X32 28

The process of breaking text into words and punctuation marks in known asTokenization

Which of the following function is used to generate a set of all possible nconsecutive words appearing in a textgrams() X#########Lancaster Stemmer returns buildPorter Stemmer returns builder. ################FINAL############################What is the output of the following expression?import nltklancaster = nltk.LancasterStemmer()print(lancaster.stem('power'))pow

What is the total number of unique words present in text collection, text6, whileConsidering characters too as words2166

What is the total number of words present in text collection, text6, whileConsidering characters too as words16967

How many words are ending with 'ing' in text collection text6?109

Count the number of words in text collection, text6, which have only digits ascharacters?24

Which of the following NLTK corpus represent a collection US presidential inauguraladdresses, starting from 1789?inaugural

Which tag occurs maximum in text collections associated with news genre of browncorpus?NN

How many number of words are obtained when the sentence Python is cool!!! istokenized into words, with regular expression r'\w+' ?3

How many number of words are obtained when the sentence Python is cool!!! istokenized into words6import nltklancaster = nltk.LancasterStemmer()print(lancaster.stem('women'))wom

Which of the following is a Text corpus structure?All of those mentioned

Which of the following module is used to download text from a HTML fileurllib

How many times does the word sugar occur in text collections, grouped into genre'sugar'? Consider reuters corpus.0

How many times does the words tonnes and year occur in text collections, groupedinto genre sugar? Consider reuters corpus.355, 196 How many times does the tag AT is associated with the word The in brown corpus?7824

How many times does the words lead and smelter occur in text collections, groupedinto genre zinc? Consider reuters corpus.40, 33

###################import retext = 'Python is cool!!!'tokens = re.findall(r'\w+', text)len(tokens)3

#get tags from brownfrom nltk.corpus import brownbrown_tagged = brown.tagged_words()1161192

import nltktext = 'Python is awesome.'words = nltk.word_tokenize(text)defined_tags = {'is':'BEZ', 'over':'IN', 'who': 'WPS'}

-------------------------------------------------------------------------------------------------------LIBRARY MANUAL:https://www.nltk.org/book/ch02.htmlONLINE CONSOLE PYTHON3:https://www.katacoda.com/courses/python/playgroundpip3 install --user setuptools && pip3 install nltkpython3 -c "import nltk; nltk.download('book')"-------------------------------------------------------------------------------------------------------- EXAMEN FINAL--------------------------------------------------------------------------------------------------------Which of the following is not a collocation, associated with text6 ?import nltkfrom nltk.book import text6gen_text = nltk.Text(text6)print(gen_text.collocations())Straight Table--------------------------------------------------------------------------------------------------------How many times does the tag AT is associated with the word The in brown corpus?import ntltkfrom nltk.corpus import brownbrown_text_tagged = nltk.corpus.brown.tagged_words()tag_fd = nltk.FreqDist(tag for (word, tag) in brown_text_tagged if tag=='AT' andword =='The')print(tag_fd)6725--------------------------------------------------------------------------------------------------------Which of the following function is used to tag parts of speech to words appearingin a text? pos_tag()--------------------------------------------------------------------------------------------------------How many words are ending with 'ly' in text collection text6?cimport nltkfrom nltk.book import text6ly_ending_words = [word for word in text6 if word.endswith('ly') ]print(len(ly_ending_words))109--------------------------------------------------------------------------------------------------------Which of the following method can be used to determine the number of textcollection files associated with a corpus?fileids()

Which of the following method can be used to view the conditions, which are usedwhile computing conditional frequency distributions?conditions()

Which of the following method can be used to determine the number of textcollection, associated with a corpus?abspath()--------------------------------------------------------------------------------------------------------Count the number of words in text collection, text6, which have only digits ascharacters?24--------------------------------------------------------------------------------------------------------Which of the following method is used to view the tagged words of text corpustagged_words()--------------------------------------------------------------------------------------------------------What is the output of the following expression?import nltklancaster = nltk.LancasterStemmer()print(lancaster.stem('lying'))lying--------------------------------------------------------------------------------------------------------What is the frequency of bigram ('HEAD', 'KNIGHT') in text collection text6import nltkfrom nltk.book import text6bigrams = nltk.bigrams(tokens)filtered_bigrams = [ (w1, w2) for w1, w2 in bigrams if w1=='HEAD' and w2=='KNIGHT']print(filtered_bigrams)29--------------------------------------------------------------------------------------------------------What is the output of the following expression ?import nltkporter = nltk.PorterStemmer()print(porter.stem('ceremony'))ceremoni--------------------------------------------------------------------------------------------------------Which of the following method is used to tokenize a text based on a regularexpressionregexp_tokenize() --------------------------------------------------------------------------------------------------------What is the frequency of word 'ARTHUR' in text collection text6 R: 0.0132import nltkfrom nltk.book import text6fdist = nltk.FreqDist(text6)print(fdist.freq('ARTHUR'))0.0132--------------------------------------------------------------------------------------------------------Which of the following function is used to obtain set of all pair of consecutivewords appearing in a text?bigrams()--------------------------------------------------------------------------------------------------------What is the range of length of words present in text collection text6?X-1 to 10--------------------------------------------------------------------------------------------------------What is the output of the following code?import res = 'Python is cool!!!'print(re.findall(r'\s\w+\b', s))[' is', ' cool']

[' is', ' cool']--------------------------------------------------------------------------------------------------------Which of the following class is used to convert your own collections of text into acorpus?PlaintextCorpusReader--------------------------------------------------------------------------------------------------------What is the output of the following expression?import nltkwnl = nltk.WordNetLemmatizer()print(wnl.lemmatize('women'))woman--------------------------------------------------------------------------------------------------------Which of the following NLTK corpus represent a collection of around 10000 newsarticles?reuters--------------------------------------------------------------------------------------------------------How many times each unique word of text6 collection is repeated on an average?X-6.5 times--------------------------------------------------------------------------------------------------------What is the frequency of bigram ('BLACK', 'KNIGHT') in text collection text6?import nltkfrom nltk.book import text6bigrams = nltk.bigrams(text6)filtered_bigrams = [ (w1, w2) for w1, w2 in bigrams if w1=='BLACK' andw2=='KNIGHT']print(len(filtered_bigrams))32-------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------- HANDS ON: 1--------------------------------------------------------------------------------------------------------pip3 install --user setuptools && pip3 install nltkpython3 -c "import nltk; nltk.download('book')"

import nltkfrom nltk.book import text6n = len(text6)print(n)

u = len(set(text6))print(u)

wc = n/uprint(wc)

ise_ending_words = [word for word in set(text6) if word.endswith('ise') ]print(len(ise_ending_words))

contains_z = len([word for word in set(text6) if 'z' in word])print(contains_z)

contains_pt = len([word for word in set(text6) if 'pt' in word])print(contains_pt)

import retitle_words = len(re.findall(r'([A-Z][a-z]+)', text6))

title_words = [word for word in set(text6) if re.search(r'([A-Z][a-z]+)', word)]

-------------------------------------------------------------------------------------------------------- HANDS ON: 2--------------------------------------------------------------------------------------------------------import nltk, refrom nltk.corpus import gutenbergfor fileid in gutenberg.fileids(): n_words = len(gutenberg.words(fileid)) n_unique_words = len(set(gutenberg.words(fileid))) word_coverage = n_words / n_unique_words print(word_coverage, fileid)

aus_words = len(gutenberg.words('austen-sense.txt))aus_words_apha = len([word for word in gutenberg.words('austen-sense.txt') ifword.isalpha()]aus_words_gt4_z = len([word for word in gutenberg.words('austen-sense.txt') ifword.isalpha() and len(word) > 4 and 'z' in word])print(aus_words_gt4_z)

---------------------------- HANDS ON: 3---------------------------------------------------------------------------import nltkfrom nltk.corpus import brownbrown_cdf = nltk.ConditionalFreqDist([ (genre,word.lower()) for genre in brown.categories() for word in brown.words(categories=genre) ])

brown_cdf.tabulate(conditions=['news', 'religion','romance'], samples=['can','could', 'may', 'might', 'must', 'will'])

from nltk.corpus import inauguralinaugural_cfd = nltk.ConditionalFreqDist( (target, fileid) for fileid in inaugural.fileids() for w in inaugural.words(fileid) for target in ['america', 'citizen'] if w.lower().startswith(target))

print(inaugural_cfd.conditions())

---------------------------------------------- HANDS ON: 4---------------------------------------------------------import nltkfrom urllib import requestfrom bs4 import BeautifulSoup

url = "https://en.wikipedia.org/wiki/Python_(programming_language)"html_content = request.urlopen(url).read()soup = BeautifulSoup(html_content, 'html.parser')n_links = len(soup.find_all('a'))print(n_links)

table = soup.find_all('table', attrs={'class':'wikitable'})rows = [elm.text for elm in table.find_all(['tr']) ]print(rows[1:])

------------------------------------------ HANDS ON: 5-------------------------------------------------------------import nltkfrom nltk.corpus import brownnews_words = brown.words(categories='news')lc_news_words = [w.lower() for w in news_words]len_news_words = [len(w) for w in lc_news_words]news_len_bigrams = list(nltk.bigrams(len_news_words))#Compute the conditional frequency of news_len_bigrams, where condition and eventrefers to length of a words.#Store the result in cfd_news#Determine the frequency of 6-letter words appearing next to a 4-letter wordcfd_news = nltk.ConditionalFreqDist(news_len_bigrams) cfd_news.tabulate(conditions=[6,4])

#############lc_news_bigrams =nltk.ConditionalFreqDist(news_len_bigrams)

#filtered_bigrams = [(w1, w2) for w1, w2 in news_len_bigrams if w1==6 and w2==4]cfd_news = nltk.FreqDist(filtered_bigrams)print(cfd_news[6,4])

#cfd_news = nltk.FreqDist((l1, l2) in news_len_bigrams if l1==6 amd l2==4)print(cfd_news[6,4])

-------------------------------------- HANDS ON: 6-----------------------------------------------------------------from nltk.corpus import brownhumor_words = brown.words(categories='humor')lc_humor_words = [word.lower() for word in humor_words]lc_humor_uniq_words = set(lc_humor_words)from nltk.corpus import wordswordlist_words = words.words()wordlist_uniq_words = set(wordlist_words)print(len(lc_humor_uniq_words))print(len(wordlist_uniq_words ))

----------------------------------- HANDS ON: 7-------------------------------

Import the text corpus brown.Extract the list of tagged words from the corpus brown.Store the result in brown_tagged_wordsGenerate trigrams of brown_tagged_words and store the result inbrown_tagged_trigrams.For every trigram of brown_tagged_trigrams, determine the tags associated with eachword.

This results in a list of tuples, where each tuple contain pos tags of 3consecutive words, occurring in text.Store the result in brown_trigram_pos_tags.Determine the frequency distribution of brown_trigram_pos_tags and store the resultin brown_trigram_pos_tags_freq.Print the number of occurrences of trigram ('JJ','NN','IN')

--------------------------------------------------------------------------------------------------------import nltkfrom nltk.corpus import brownbrown_tagged_words = [word for (word, tag) in nltk.corpus.brown.tagged_words()]brown_tagged_trigrams = list(nltk.trigrams(brown_tagged_words))brown_trigram_pos_tags = list() for trigram in brown_tagged_trigrams: trigram_tagged = nltk.pos_tag(trigram) tags = [tag for (word, tag) in trigram_tagged] brown_trigram_pos_tags.append(tags)

brown_trigram_pos_tags_freq = nltk.FreqDist((t1,t2,t3) for (t1,t2,t3) inbrown_trigram_pos_tags)print(brown_trigram_pos_tags_freq['JJ','NN','IN'])

brown_trigram_pos_tags_freq = nltk.FreqDist(t1,t2,t3) for (t1,t2,t3) inbrown_trigram_pos_tags if t1=='JJ' and t2=='NN' and t3=='IN')--------------------------------------------------------------------------------------------------------import nltkfrom nltk.corpus import brownbrown_tagged_words = [word for (word, tag) innltk.corpus.brown.tagged_words()]brown_tagged_trigrams = list(nltk.trigrams(brown_tagged_words))brown_trigram_pos_tags = [ nltk.pos_tag(t) for t in brown_tagged_trigrams ]brown_trigram_pos_tags_freq = nltk.FreqDist(t1,t2,t3) for (t1,t2,t3) inbrown_trigram_pos_tags if t1=='JJ' and t2=='NN' and t3=='IN')

#TASK2import nltkfrom nltk.corpus import brownbrown_tagged_words = nltk.corpus.brown.tagged_words()brown_tagged_trigrams = list(nltk.trigrams(brown_tagged_words))#[(('The', 'AT'), ('Fulton', 'NP-TL'), ('County', 'NN-TL'))]brown_trigram_pos_tags = list()for tuple in brown_tagged_trigrams: tags = [tag for (word, tag) in tuple] brown_trigram_pos_tags.append(tags)#[['AT', 'NP-TL', 'NN-TL']]brown_trigram_pos_tags_freq = nltk.FreqDist((t1,t2,t3) for (t1,t2,t3) inbrown_trigram_pos_tags)print(brown_trigram_pos_tags_freq['JJ','NN','IN'])#TASK2import nltkfrom nltk.corpus import brownbrown_tagged_sents = nltk.corpus.brown.tagged_sents()total_size = len(brown_tagged_sents)train_size = int(total_size * 0.8)train_sents = brown_tagged_sents[:train_size]test_sents = brown_tagged_sents[train_size:]unigram_tagger = nltk.UnigramTagger(train_sents)tag_performace = unigram_tagger.evaluate(test_sents)print(tag_performace)

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