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Adjective_filter.py
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Adjective_filter.py
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# 24-10-2018 | THILINA_CHATHURANGA @ Campus
import codecs
import re
import os
part_no = 26
def get_adjectives(response_text):
words = re.split(' ', response_text, re.UNICODE)
# Noise Removed | NR
f = codecs.open("D:\\Education\\Z\\Filtered\\ADJECTIVES_NR" + str(part_no) + ".TXT", "a", encoding='utf-8')
for word in words:
# With findall() sometimes retrieve sentences appending the _JJ.
# To remove that noise, if word count is not 1, take only the last word.
if re.findall('.{1,}_JJ', word):
if len(re.split(' ', word)) != 1:
adj_with_noise = re.split('_JJ', word)[0]
adj = re.split(' ', adj_with_noise)[-1]
# adj = re.split('_JJ', last_word)[0]
else:
adj = re.split('_JJ', word)[0]
f.write(str(adj) + '\r\n')
f.close()
def scrap_adjectives(file_name):
corpus_file_path = "D:\\Education\\Z\\Tagged-Corpus\\V2\\PART" + str(part_no) + "\\" + file_name + ".TXT"
print('[Filtering ' + file_name + ']')
with codecs.open(corpus_file_path, encoding="utf-8") as fp:
line = fp.readline()
count = 10
while line:
line = fp.readline()
# print('Line' + str(count) + ' > ', line)
get_adjectives(line)
count += 1
directory_path = "D:\\Education\\Z\\Tagged-Corpus\\V2\\PART" + str(part_no)
for filename in os.listdir(directory_path):
file_name_str = filename.title().upper().split('.')
scrap_adjectives(file_name_str[0])