NLP Python

Question 1

Function for importing

Answer 1

import

Question 2

Function for opening nltk downloader

Answer 2

nltk.download()

Question 3

Function for importing nltk

Answer 3

import nltk

Question 4

Function for importing NLTK’s book module

Answer 4

from nltk.book import*

Question 5

Function for pulling up the name of text 1

Answer 5

text1

Question 6

Function for finding every occurrence of a given word

Answer 6

.concordance()

Question 7

Finding every occurrence of a given word example

Answer 7

text2.concordance(“monstrous”)

Question 8

Function for finding other words used in a similar range of contexts

Answer 8

.similar()

Question 9

Finding other words used in a similar range of contexts example

Answer 9

text1.similar(“monstrous”)

Question 10

Function which examines the shared contexts of two or more words

Answer 10

.common_contexts([])

Question 11

Examining the shared contexts of two or more words example

Answer 11

text2.common_contexts([“monstrous”, “very”])

Question 12

Dispersion plot definition

Answer 12

A plot which shows where words occur in a text

Question 13

Dispersion plot function

Answer 13

.dispersion_plot([])

Question 14

Dispersion plot example

Answer 14

text4.dispersion_plot([“citizens”, “democracy”])

Question 15

Function for generating random text

Answer 15

.generate()

Question 16

Generating random text example

Answer 16

text3.generate()

Question 17

Function for generating real random text

Answer 17

import random

.generate(random_seed=random.random())

Question 18

Real random text generator example

Answer 18

import random

text3.generate(random_seed=random.random())

Question 19

Function for counting words and symbols in a text

Answer 19

len()

Question 20

Token definition

Answer 20

a sequence of characters such as hairy, his or :) that we want to treat as a group

Question 21

Function to sort a list of vocabulary items

Answer 21

sorted()

Question 22

Word type definition

Answer 22

unique items of vocabulary

Question 23

Function to create a list of all the unique words in a text

Answer 23

set()

Question 24

Creating a list of all the unique words in a text example

Answer 24

set(text3)

Question 25

Function to create a sorted list of all the unique words in a text

Answer 25

sorted(set())

Question 26

Creating sorted list of all the unique words in a text example

Answer 26

sorted(set(text3))

Question 27

Function to calculate how many times each word is used on average

Answer 27

len() / len(set())

Question 28

Calculating how many times each word is used on average example

Answer 28

len(text3) / len(set(text3))

Question 29

Function to count how often a word occurs in a text

Answer 29

.count()

Question 30

Counting number of times a word appears example

Answer 30

text3.count(“smote”)

Question 31

Function to find what percentage of a text is taken up by a specific word

Answer 31

100 * .count() / len()

Question 32

Finding what percentage of a text is taken up by a specific word example

Answer 32

100 * text4.count(‘a’) / len(text4)

Question 33

Parameter definition

Answer 33

a placeholder for a variable which can be entered as an argument to a function

Question 34

Argument definition

Answer 34

The thing in a function which we place in the parentheses

Question 35

Function for defining a function

Answer 35

def

Question 36

List operator

Answer 36

[ ]

Question 37

Concatenation operator

Answer 37

+

Question 38

Function to add an item to a list

Answer 38

.append()

Question 39

Index operator

Answer 39

[ ]

Question 40

Index definition

Answer 40

The number in which an item in a list occurs

Question 41

Function for finding an item in a list

Answer 41

.index()

Question 42

Function for finding an item in a list example

Answer 42

text4.index(‘awaken’)

Question 43

Slicing operator

Answer 43

[ : ]

Question 44

Operator to set a variable

Answer 44

=

Question 45

Frequency distribution definition

Answer 45

Counts the frequency of each vocabulary item in a text

Question 46

Frequency distribution function

Answer 46

FreqDist()

Question 47

Function to pull up only the keys of a dictionary

Answer 47

.keys()

Question 48

Hapax definition

Answer 48

A word occurring only once in a document

Question 49

Function for viewing hapaxes

Answer 49

.hapaxes()

Question 50

“The set of all w such that w is an element of V”

Answer 50

[w for w in V]

Question 51

“Property of w”

Answer 51

P(w)

Question 52

“The set of all w such that w is an element of V and w has property P”

Answer 52

[w for w in V if p(w)]

Question 53

Function for finding all the long words in a text

Answer 53

[w for w in V if len(w) > 15]

Question 54

Function to find words that occur more than 7 times

Answer 54

[w for w in set(text5) if fdist5[w] > 7]

Question 55

Function to combine multiple words into a single string

Answer 55

.join()

Question 56

Function to combine multiple words into a single string example

Answer 56

‘ ‘.join([‘Monty’, ‘Python’])

Question 57

Function to split a string into a list

Answer 57

.split()

Question 58

Function to split a string into a list example

Answer 58

‘Monty Python’.split()

Question 59

Collocation definition

Answer 59

a sequence of words that occur together unusually often (ex. red wine)

Question 60

Function to find a sequence of words that occur together unusually often

Answer 60

.collocations()

Question 61

Bigram definition

Answer 61

word pairs that occur next to each other in a text. They may or may not occur together frequently

Question 62

Function to find word pairs that occur next to each other in a text

Answer 62

list(bigrams())

Question 63

Anaphora resolution definition

Answer 63

Identifying what a pronoun or noun phrase refers to

Question 64

Semantic role labeling definition

Answer 64

Identifying how a noun phrase relates to the verb (agent, patient, etc)

Question 65

Function to create a list with a given start and stop point

Answer 65

range()

Question 66

Three parameters for range

Answer 66

range(start, stop, step)