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logical_equivalence_synthetic_testset_change_name.py
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logical_equivalence_synthetic_testset_change_name.py
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import pandas as pd
import random
from nltk.corpus import wordnet
from itertools import combinations, permutations
data = []
df_output = pd.DataFrame(data,columns=['ID','Sentence1','Sentence2', 'Label', 'Tag'])
subject_list = ['the sheep', 'the kitten', 'the Garfield', 'the lion', 'the goat', 'the bull', 'the cow',
'the elephant', 'the butterfly', 'the fish',
'Peter', 'Bill', 'Tom', 'Amy', 'Charles', 'Tim', 'Lucy', 'John']
verb_list = ['is']
adjective_list = ['kind', 'quiet', 'round', 'nice', 'smart', 'clever',
'dull', 'rough', 'lazy', 'slow', 'sleepy', 'boring', 'tired', 'reckless',
'furry', 'small', 'cute', 'lovely', 'beautiful', 'funny',
'big', 'strong', 'awful', 'fierce', 'heavy', 'horrible', 'powerful', 'angry',
'high', 'huge',
'short', 'thin', 'little', 'tiny',
'wealthy', 'poor', 'dull', 'rough', 'bad', 'sad']
def double_negation(df_output, id, sub, verb, adj):
##Logical equivalence example
s1 = sub + " " + verb + " " + adj + "."
syn = wordnet.synsets(adj)[0]
good = wordnet.synset(syn.name())
antonym = good.lemmas()[0].antonyms()
if len(antonym) > 0:
s2 = sub + " " + verb + " not " + antonym[0].name() + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Double Negation"}, ignore_index=True)
s3 = sub + " " + verb + " not " + adj + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Double Negation"}, ignore_index=True)
return df_output
def commutative(df_output, id, sub1, verb1, adj1, sub2, verb2, adj2):
##Logical equivalence example
s1 = sub1 + " " + verb1 + " " + adj1
s2 = sub2 + " " + verb2 + " " + adj2
s3 = sub1 + " " + verb1 + " not " + adj1
concat_sen = s1 + " and " + s2 + "."
concat_sen2 = s2 + " and " + s1 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': concat_sen,
'Sentence2': concat_sen2,
'Label': 1,
'Tag': "Commutative"}, ignore_index=True)
concat_sen3 = s1 + " and " + s3 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': concat_sen,
'Sentence2': concat_sen3,
'Label': 0,
'Tag': "Commutative"}, ignore_index=True)
return df_output
def contraposition(df_output, id, sub1, sub2, verb, adj1, adj2):
##Logical equivalence example
s1 = "If " + sub1 + " " + verb + " " + adj1 + ", then " + sub2 + " " + verb + " " + adj2 + "."
s2 = "If " + sub2 + " " + verb + " not " + adj2 + ", then " + sub1 + " " + verb + " not " + adj1 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Contraposition"}, ignore_index=True)
s3 = "If " + sub1 + " " + verb + " " + adj1 + ", then " + sub2 + " " + verb + " not " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Contraposition"}, ignore_index=True)
s1 = "If " + sub1 + " " + verb + " " + adj1 + ", then " + sub2 + " " + verb + " not " + adj2 + "."
s2 = "If " + sub2 + " " + verb + " " + adj2 + ", then " + sub1 + " " + verb + " not " + adj1 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Contraposition"}, ignore_index=True)
s3 = "If " + sub1 + " " + verb + " " + adj1 + ", then " + sub2 + " " + verb + " " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Contraposition"}, ignore_index=True)
s1 = "If " + sub1 + " " + verb + " not " + adj1 + ", then " + sub2 + " " + verb + " " + adj2 + "."
s2 = "If " + sub2 + " " + verb + " not " + adj2 + ", then " + sub1 + " " + verb + " " + adj1 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Contraposition"}, ignore_index=True)
s3 = "If " + sub1 + " " + verb + " not " + adj1 + ", then " + sub2 + " " + verb + " not " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Contraposition"}, ignore_index=True)
s1 = "If " + sub1 + " " + verb + " not " + adj1 + ", then " + sub2 + " " + verb + " not " + adj2 + "."
s2 = "If " + sub2 + " " + verb + " not " + adj2 + ", then " + sub1 + " " + verb + " not " + adj1 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Contraposition"}, ignore_index=True)
s3 = "If " + sub1 + " " + verb + " not " + adj1 + ", then " + sub2 + " " + verb + " " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Contraposition"}, ignore_index=True)
return df_output
def implication(df_output, id, sub1, sub2, verb, adj1, adj2):
##Logical equivalence example
s1 = "If " + sub1 + " " + verb + " " + adj1 + ", then " + sub2 + " " + verb + " " + adj2 + "."
s2 = sub1 + " " + verb + " not " + adj1 + " or " + sub2 + " " + verb + " " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s2,
'Label': 1,
'Tag': "Contraposition"}, ignore_index=True)
s3 = sub1 + " " + verb + " not " + adj1 + " or " + sub2 + " " + verb + " not " + adj2 + "."
df_output = df_output.append(
{'ID': id,
'Sentence1': s1,
'Sentence2': s3,
'Label': 0,
'Tag': "Contraposition"}, ignore_index=True)
return df_output
id = 0
for i in range(100):
random_number_1 = random.randint(0, len(subject_list) - 1)
random_number_2 = random.randint(0, len(adjective_list) - 1)
subject_1 = subject_list[random_number_1]
adjective_1 = adjective_list[random_number_1]
df_output = double_negation(df_output, id, subject_1, verb_list[0], adjective_1)
id = id + 1
for i in range(100):
random_number_1 = random.randint(0, len(subject_list) - 1)
random_number_2 = random.randint(0, len(adjective_list) - 1)
subject_1 = subject_list[random_number_1]
adjective_1 = adjective_list[random_number_1]
random_number_3 = random.randint(0, len(subject_list) - 1)
random_number_4 = random.randint(0, len(adjective_list) - 1)
while random_number_3 == random_number_1:
random_number_3 = random.randint(0, len(subject_list) - 1)
while random_number_4 == random_number_2:
random_number_4 = random.randint(0, len(adjective_list) - 1)
subject_3 = subject_list[random_number_3]
adjective_4 = adjective_list[random_number_4]
df_output = commutative(df_output, id, subject_1, verb_list[0], adjective_1, subject_3, verb_list[0], adjective_4)
id = id + 1
for i in range(100):
random_number_1 = random.randint(0, len(subject_list) - 1)
random_number_2 = random.randint(0, len(subject_list) - 1)
while random_number_1 == random_number_2:
random_number_2 = random.randint(0, len(subject_list) - 1)
subject_1 = subject_list[random_number_1]
subject_2 = subject_list[random_number_2]
random_number_1 = random.randint(0, len(adjective_list) - 1)
random_number_2 = random.randint(0, len(adjective_list) - 1)
adjective_1 = adjective_list[random_number_1]
adjective_2 = adjective_list[random_number_2]
## comtraposition logical equivalence/inequivalence
df_output = contraposition(df_output, id, subject_1, subject_2, verb_list[0], adjective_1, adjective_2)
id = id + 1
for i in range(100):
random_number_1 = random.randint(0, len(subject_list) - 1)
random_number_2 = random.randint(0, len(subject_list) - 1)
while random_number_1 == random_number_2:
random_number_2 = random.randint(0, len(subject_list) - 1)
subject_1 = subject_list[random_number_1]
subject_2 = subject_list[random_number_2]
random_number_1 = random.randint(0, len(adjective_list) - 1)
random_number_2 = random.randint(0, len(adjective_list) - 1)
adjective_1 = adjective_list[random_number_1]
adjective_2 = adjective_list[random_number_2]
## comtraposition logical equivalence/inequivalence
df_output = implication(df_output, id, subject_1, subject_2, verb_list[0], adjective_1, adjective_2)
id = id + 1
df_output.to_csv("./synthetic_logical_equivalence_sentence_pair_testset_change_name.csv",index = None,encoding = 'utf8')