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# -*- coding: utf-8 -*-
import re
import nltk
import Levenshtein
from App.bin import constants
class ParameterExtractor(object):
def __init__(self, sentence):
self.sentence = sentence
def clean_parameter(self, parameter):
line = re.sub(r'\s[a-zA-Z]$', r'', parameter)
line = line.strip()
return line
def extract_parameters(self):
sentence = self.sentence
parameters_list = []
with open(constants.ASSETS + "parameter_core", 'r') as l:
words_list = l.read().splitlines()
match_word = re.compile(r'(\b(?:%s)\b)' % '|'.join(words_list))
with open(constants.ASSETS + "exclude_from_parameters", 'r') as m:
not_included_words_list = m.read().splitlines()
match_not_included_word = re.compile(r'(\b(?:%s)\b)' % '|'.join(not_included_words_list))
parameter_indice = re.search(match_word, sentence)
if parameter_indice:
words = nltk.word_tokenize(sentence)
sentence = nltk.pos_tag(words)
grammar = """PARAMETER:{<NN>+<IN><DT>?<NN.*>+}
{<NN*>+}
"""
parameter_parser = nltk.RegexpParser(grammar)
tree = parameter_parser.parse(sentence)
for subtree in tree.subtrees():
if subtree.label() == 'PARAMETER':
parameter_candidate = " ".join(word for word, tag in subtree.leaves())
parameter_candidate_indice = re.search(match_word, parameter_candidate)
not_parameter = re.search(match_not_included_word, parameter_candidate)
if parameter_candidate_indice and not not_parameter :
#parameter_candidate=self.clean_parameter(parameter_candidate)
parameters_list.append(parameter_candidate)
parameters_list = list(set(parameters_list))
return list(parameters_list)
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