def prepareSentence2(sentence):
sentenceParseResult = parse_text(sentence)
sentenceLemmatized = lemmatize(sentenceParseResult)
sentencePosTagged = posTag(sentenceParseResult)
sentenceLemmasAndPosTags = []
for i in range(len(sentenceLemmatized)):
sentenceLemmasAndPosTags.append([])
for i in range(len(sentenceLemmatized)):
for item in sentenceLemmatized[i]:
sentenceLemmasAndPosTags[i].append(item)
sentenceLemmasAndPosTags[i].append(sentencePosTagged[i][3])
words = []
for rawWord in sentenceLemmasAndPosTags:
word = Word(rawWord[1] - 1, rawWord[2])
word.lemma = rawWord[3]
word.pos = rawWord[4]
words.append(word)
return words
def _get_words(raw_sentence):
words = []
for i, item in enumerate(raw_sentence['words']):
word = Word(i + 1, item[0])
word.lemma = item[1]['Lemma']
word.pos = item[1]['PartOfSpeech'].lower()
word.ner = item[1]['NamedEntityTag']
words.append(word)
return words
def load(path_input):
sentences = []
sentence = []
with codecs.open(path_input,'r', 'utf8') as f:
lines = f.readlines()
for line in lines:
if line == '\n':
sentences.append(sentence)
sentence = []
continue
parts = line.strip().split('\t')
word = Word(parts[0], parts[1]) # punctuation head is root
word.lemma = parts[2]
word.pos = parts[4]
word.dep = parts[7]
word.head = parts[6]
sentence.append(word)
sentences.append(sentence)
return sentences
