lineList = [
line for line in open(r'results_desire.tsv', 'r', encoding='utf-8')
]
f = open(r"sample_desire.tsv", "w", encoding='utf-8')
filtered_lines = []
for s in range(1, len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['desire', 'desired']
if not (fl.isGerund(my_split) or fl.hasGerundAfter(my_split, my_tokens)
or fl.isIntransitive(my_split, tagged_tokens)
or fl.hasToAfterVerb(my_split, my_tokens) or fl.isAdjectiveOrNoun(
my_split, my_tokens, tagged_tokens, formlist)
or tagged_tokens[int(my_split[5]) + 1][1].startswith('VB') or
(my_tokens[int(my_split[3]) + 1].lower() == 'to'
and tagged_tokens[int(my_split[3]) + 2][1] == 'VB')):
filtered_lines.append(lineList[s])
n = 0
sampled_numbers = []
while n < 100:
s = random.randint(1, len(filtered_lines))
if not s in sampled_numbers:
sampled_numbers.append(s)
my_split = filtered_lines[s].split('\t')
if not fl.verbHasXcomp(my_split):
f.write(filtered_lines[s])
#filters out phrases like 'Sunny is a much loved figure in the campus community .'
def lovedAsNounModifyer(my_split, my_tokens, tagged_tokens):
if (my_split[2].lower() == 'loved') and ((tagged_tokens[int(my_split[5])-2][1] in ['DT','PRP$','CC'] and (tagged_tokens[int(my_split[5])-1][1].startswith('RB') or tagged_tokens[int(my_split[5])-1][0].lower() in ['well','most','much'] ) and (tagged_tokens[int(my_split[5])+1][1].startswith(('NN','JJ')))) or tagged_tokens[int(my_split[5])+1][0].lower in ['one','ones']):
# print(my_split[7])
return(True)
else:
return (False)
lineList = [line for line in open(r'results_love.tsv', 'r', encoding='utf-8')]
f = open(r"sample_love.tsv", "w",encoding='utf-8')
filtered_lines = []
for s in range (1,len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['love','loves']
if not (fl.hasPattern(my_split[7],'\slove\slife') or lovedAsNounModifyer(my_split, my_tokens, tagged_tokens) or fl.isGerund (my_split) or fl.hasGerundAfter(my_split, my_tokens) or fl.isAdjectiveOrNoun(my_split, my_tokens, tagged_tokens, formlist) or fl.hasToAfterVerb(my_split, my_tokens) or (fl.hasPattern(my_split[7], "would\shave\sloved") and my_tokens[int(my_split[3])+1] == 'to')):
filtered_lines.append(lineList[s])
sampleNumbers = random.sample(range(1, len(filtered_lines)), 100)
for s in range (len(filtered_lines)):
if s in sampleNumbers:
f.write(filtered_lines[s])
f.close()
import nltk
import sys
sys.path.insert(0, '..')
import filter_lines as fl
lineList = [
line for line in open(r'results_detest.tsv', 'r', encoding='utf-8')
]
f = open(r"sample_detest.tsv", "w", encoding='utf-8')
filtered_lines = []
for s in range(1, len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['detested']
if not (fl.isGerund(my_split) or fl.hasGerundAfter(my_split, my_tokens) or
fl.isAdjectiveOrNoun(my_split, my_tokens, tagged_tokens, formlist)
or fl.hasPattern(my_split[7].lower(),
"\s(much|most|widely|her)\sdetested")):
filtered_lines.append(lineList[s])
sampleNumbers = random.sample(range(1, len(filtered_lines)), 100)
for s in range(len(filtered_lines)):
if s in sampleNumbers:
f.write(filtered_lines[s])
f.close()
lineList = [line for line in open(r'results_resent.tsv', 'r', encoding='utf-8')]
f = open(r"sample_resent.tsv", "w",encoding='utf-8')
filtered_lines = []
for s in range (1,len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['resented']
if not (fl.isGerund (my_split) or fl.hasGerundAfter(my_split, my_tokens) or fl.isAdjectiveOrNoun(my_split, my_tokens, tagged_tokens, formlist) or fl.hasToAfterVerb(my_split, my_tokens)):
filtered_lines.append(lineList[s])
n = 0
sampled_numbers = []
while n < 100:
s = random.randint(1, len(filtered_lines))
if not s in sampled_numbers:
sampled_numbers.append(s)
my_split = filtered_lines[s].split('\t')
import re
import nltk
import sys
sys.path.insert(0,'..')
import filter_lines as fl
lineList = [line for line in open(r'results_like.tsv', 'r', encoding='utf-8')]
f = open(r"sample_like.tsv", "w",encoding='utf-8')
filtered_lines = []
for s in range (1,len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['like', 'likes']
if not (fl.isGerund (my_split) or fl.hasGerundAfter(my_split, my_tokens) or fl.hasPattern(my_split[7].lower(), ",\slike\s") or fl.hasPattern(my_split[7].lower(), "just\slike\s") or fl.hasToAfterVerb(my_split, my_tokens) or (fl.hasPattern(my_split[7], "would\shave\sliked") and my_tokens[int(my_split[3])+1] == 'to') or (my_tokens[int(my_split[5])-1] in ['be','was','were','am','are','is']) or(my_tokens[int(my_split[5])-2] in ['be','was','were','am','are','is'] and my_tokens[int(my_split[5])-1] == 'not') or fl.isAdjectiveOrNoun(my_split, my_tokens, tagged_tokens, formlist)):
filtered_lines.append(lineList[s])
sampleNumbers = random.sample(range(1, len(filtered_lines)), 100)
for s in range (len(filtered_lines)):
if s in sampleNumbers:
f.write(filtered_lines[s])
f.close()
import random
import re
import nltk
import sys
sys.path.insert(0, '..')
import filter_lines as fl
lineList = [line for line in open(r'results_dread.tsv', 'r', encoding='utf-8')]
f = open(r"sample_dread.tsv", "w", encoding='utf-8')
filtered_lines = []
for s in range(1, len(lineList)):
my_split = lineList[s].split('\t')
my_tokens = my_split[7].split(' ')
tagged_tokens = nltk.pos_tag(my_tokens)
formlist = ['dreaded', 'dread']
if not (fl.isGerund(my_split)
or fl.hasGerundAfter(my_split, my_tokens) or fl.isAdjectiveOrNoun(
my_split, my_tokens, tagged_tokens, formlist)):
filtered_lines.append(lineList[s])
sampleNumbers = random.sample(range(1, len(filtered_lines)), 100)
for s in range(len(filtered_lines)):
if s in sampleNumbers:
f.write(filtered_lines[s])
f.close()
