61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
''' This module contains the class
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for generating incorrect alternative
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answers for a given answer
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'''
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import gensim
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import gensim.downloader as api
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from gensim.models import Word2Vec
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from nltk.tokenize import sent_tokenize, word_tokenize
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import random
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import numpy as np
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class IncorrectAnswerGenerator:
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''' This class contains the methods
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for generating the incorrect answers
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given an answer
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'''
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def __init__(self, document):
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# model required to fetch similar words
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self.model = api.load("glove-wiki-gigaword-100")
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self.all_words = []
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for sent in sent_tokenize(document):
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self.all_words.extend(word_tokenize(sent))
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self.all_words = list(set(self.all_words))
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def get_all_options_dict(self, answer, num_options):
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''' This method returns a dict
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of 'num_options' options out of
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which one is correct and is the answer
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'''
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options_dict = dict()
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try:
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similar_words = self.model.similar_by_word(answer, topn=15)[::-1]
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for i in range(1, num_options + 1):
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options_dict[i] = similar_words[i - 1][0]
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except:
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self.all_sim = []
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for word in self.all_words:
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if word not in answer:
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try:
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self.all_sim.append(
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(self.model.similarity(answer, word), word))
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except:
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self.all_sim.append(
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(0.0, word))
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else:
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self.all_sim.append((-1.0, word))
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self.all_sim.sort(reverse=True)
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for i in range(1, num_options+1):
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options_dict[i] = self.all_sim[i-1][1]
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replacement_idx = random.randint(1, num_options)
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options_dict[replacement_idx] = answer
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return options_dict
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