def clean_twitter(phrase):
phrase = re.sub(r'(.)\1{2,}', r'\1\1', re.sub(r'[^\x00-\x7f]', ' ', phrase))
if is_bad_word(phrase.lower()):
return
parts = en_nl.tokenize(phrase).split()
for part in itertools.chain(parts, english_window(parts)):
if part.startswith(('#', '@', 'http:')):
yield part
elif part.strip() and part != 'rt' and not en_nl.is_stopword(part):
part = en_nl.normalize(part).strip('-')
if part.strip():
yield part
def get_sentences(self):
words = en_nl.tokenize(self.text).split()
sentences = []
current_sentence = []
for word in words:
if word in PUNCTUATION:
if len(current_sentence) >= 1:
sentences.append(current_sentence)
current_sentence = []
else:
current_sentence.append(word)
sentences.append(current_sentence)
return sentences
def get_sentences(self):
words = en_nl.tokenize(self.text).split()
sentences = []
current_sentence = []
for word in words:
if word in PUNCTUATION:
if len(current_sentence) >= 1:
sentences.append(current_sentence)
current_sentence = []
else:
current_sentence.append(word)
sentences.append(current_sentence)
return sentences
def clean_twitter(phrase):
phrase = re.sub(r'(.)\1{2,}', r'\1\1', re.sub(r'[^\x00-\x7f]', ' ',
phrase))
if is_bad_word(phrase.lower()):
return
parts = en_nl.tokenize(phrase).split()
for part in itertools.chain(parts, english_window(parts)):
if part.startswith(('#', '@', 'http:')):
yield part
elif part.strip() and part != 'rt' and not en_nl.is_stopword(part):
part = en_nl.normalize(part).strip('-')
if part.strip():
yield part
def extract_concepts_with_negation(text):
words = en_nl.tokenize(text).split()
return extract_concepts_from_words(words)
def extract_concepts_with_negation(text):
words = en_nl.tokenize(text).split()
return extract_concepts_from_words(words)
