def process_for_named_entity(text,
language,
to_ascii=True,
stem=False,
shorten=False):
if language == "ro":
if isinstance(text, list):
text = [replace_diactitics(subtext) for subtext in text]
else:
text = replace_diactitics(text)
if isinstance(text, list):
if to_ascii:
text = [
unicodedata.normalize('NFKD',
subtext).encode('ascii',
'ignore').decode("ascii")
for subtext in text
]
text = [subtext.lower() for subtext in text]
else:
if to_ascii:
text = unicodedata.normalize('NFKD',
text).encode('ascii',
'ignore').decode("ascii")
text = text.lower()
if language == "ro":
stemmer = snowball.RomanianStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
elif language == "it":
stemmer = snowball.ItalianStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
elif language == "en":
stemmer = snowball.EnglishStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
else:
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
if isinstance(text, list):
for i in range(len(words)):
sent = words[i]
sentence = []
if stem:
for word in sent:
word = re.sub("[^a-z0-9]", "", word)
if word != '':
sentence.append(stemmer.stem(word))
else:
for word in sent:
word = re.sub("[^a-z0-9]", "", word)
if word != '':
sentence.append(word)
procced_text.append(sentence)
else:
for word in words:
word = re.sub("[^a-z0-9]", "", word)
if word != '':
if stem:
word = stemmer.stem(word)
procced_text.append(word)
if isinstance(text, list):
for i in range(len(procced_text)):
company_name = procced_text[i]
if len(company_name) > 0 and company_name[0] != 'null':
if False and company_name[-1] in [
'srl', 'ltd', 'spa', 'ltda', 'sl', 'snc'
]:
contracted = ' '.join(company_name[:-1])
if not check_if_text_in_language(
company_name[:-1]
) and len(contracted) > 6 and not is_number(
contracted) and contracted not in [
'data', 'aprile', 'group', 'azienda',
'profilo', 'alumino', 'stato', 'roma',
'service', 'area', 'estate', 'date 4', 'work',
'altre', 'italia', 'stage', 'ottobre 2008',
'strada', '16 luglio', 'espresso', 'export',
'prime', 'sala', 'panelli'
]:
del company_name[-1]
if shorten:
while len(contracted) > 23:
if len(contracted) - len(company_name[0]) < 15:
break
del company_name[0]
contracted = ' '.join(procced_text)
procced_text[i] = ' '.join(company_name)
else:
if len(procced_text) > 0 and procced_text[0] != 'null':
if False and procced_text[-1] in [
'srl', 'ltd', 'spa', 'ltda', 'sl', 'snc'
]:
contracted = ' '.join(procced_text[:-1])
if not check_if_text_in_language(procced_text[:-1]) and len(
contracted) > 6 and not is_number(
contracted) and contracted not in [
'data', 'aprile', 'group', 'azienda',
'profilo', 'allumino', 'stato', 'roma',
'service', 'area', 'estate', 'metalmeccanica'
'date 4', 'work', 'castel'
'altre', 'italia', 'controlo qualita', 'stage',
'ottobre 2008', 'atena', 'strada', '16 luglio',
'industriale', 'espresso', 'export', 'prime',
'sala', 'panelli'
]:
del procced_text[-1]
if shorten:
while len(contracted) > 23:
if len(contracted) - len(procced_text[0]) < 15:
break
del procced_text[0]
contracted = ' '.join(procced_text)
procced_text = ' '.join(procced_text)
return procced_text
def process_words(text,
language=None,
stem=True,
to_ascii=True,
character_level=False):
if language is None:
translator = Translator()
if isinstance(text, list):
language = translator.detect(text)[0].lang
if language == "ro":
if isinstance(text, list):
text = [replace_diactitics(subtext) for subtext in text]
else:
text = replace_diactitics(text)
if isinstance(text, list):
if to_ascii:
text = [
unicodedata.normalize('NFKD',
subtext).encode('ascii',
'ignore').decode("ascii")
for subtext in text
]
text = [subtext.lower() for subtext in text]
else:
if to_ascii:
text = unicodedata.normalize('NFKD',
text).encode('ascii',
'ignore').decode("ascii")
text = text.lower()
if language == "ro":
stemmer = snowball.RomanianStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
elif language == "it":
stemmer = snowball.ItalianStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
elif language == "en":
stemmer = snowball.EnglishStemmer()
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
else:
if isinstance(text, list):
words = [nltk.word_tokenize(subtext) for subtext in text]
else:
words = nltk.word_tokenize(text)
procced_text = []
stopw = []
if language in stopwords:
stopw = stopwords[language]
if isinstance(text, list):
for i in range(len(words)):
sent = words[i]
sentence = []
if stem:
for word in sent:
word = keep_only_letters(word)
if word not in stopw:
if character_level:
sentence += list(word)
else:
sentence.append(stemmer.stem(word))
else:
for word in sent:
word = keep_only_letters(word)
if word not in stopw:
if character_level:
sentence += list(word)
else:
sentence.append(word)
procced_text.append(sentence)
else:
for word in words:
word = keep_only_letters(word)
if word not in stopw:
if character_level:
procced_text += list(word)
else:
procced_text.append(word)
return procced_text
def __init__(self):
self.stemming = snowball.ItalianStemmer()
self.tagger = treetaggerwrapper.TreeTagger(TAGLANG='it')