def apply(self, doc):
for sentence in doc.sentences:
text = sentence.text.lower().replace('_', ' ')
prefixes = ['họ tên', 'họ và tên']
check = True
for prefix in prefixes:
start = text.find(prefix)
if start != -1:
# Trường hợp câu chứa tiền tố là "họ tên" nhưng bị tách làm 2
if start + len(prefix) + 5 >= len(text):
check = False
continue
# Trường hợp "họ tên : ABCxyz"
elif text.find(': ') != -1:
start = text.find(': ') + 2
else:
start += len(prefix) + 1
check = False
yield TemporarySpanMention(char_start=start,
char_end=len(text) - 1,
sentence=sentence)
if check:
yield TemporarySpanMention(char_start=0,
char_end=len(text) - 1,
sentence=sentence)
def apply(self, context: Sentence) -> Iterator[TemporarySpanMention]:
# These are the character offset--**relative to the sentence
# start**--for each _token_
offsets = context.char_offsets
# Loop over all n-grams in **reverse** order (to facilitate
# longest-match semantics)
L = len(offsets)
seen: Set[TemporarySpanMention] = set()
for j in range(self.n_min, self.n_max + 1)[::-1]:
for i in range(L - j + 1):
w = context.words[i + j - 1]
start = offsets[i]
end = offsets[i + j - 1] + len(w) - 1
ts = TemporarySpanMention(
char_start=start, char_end=end, sentence=context
)
if ts not in seen:
seen.add(ts)
yield ts
# Check for split
if (
j == 1
and self.n_max >= 1
and self.n_min <= 1
and self.split_rgx is not None
and end - start > 0
):
text = context.text[start - offsets[0] : end - offsets[0] + 1]
start_idxs = [0]
end_idxs = []
for m in re.finditer(self.split_rgx, text):
start_idxs.append(m.end())
end_idxs.append(m.start())
end_idxs.append(len(text))
for start_idx in start_idxs:
for end_idx in end_idxs:
if start_idx < end_idx:
ts = TemporarySpanMention(
char_start=start_idx,
char_end=end_idx - 1,
sentence=context,
)
if ts not in seen and ts.get_span():
seen.add(ts)
yield ts
def apply(self, doc):
list_digit = ['0','1','2','3','4','5','6','7','8','9']
symbol_plus = '+'
sympol_bracket = "(+"
start_rgx = r'(\d|\+|\(\+)'
number_phone = '([(]?\+84[)]?[ ]*\d{1,3}|0\d{2,4})[ ]?(-|\.)?[ ]?\d{3,4}[ ]?(-|\.)?[ ]?\d{3,4}'
for sentence in doc.sentences:
text = sentence.text
matches = re.finditer(start_rgx, text)
if matches is None:
start = -1
else:
for match in matches:
start = match.start()
end = -1
for i in range(len(text)-1, 0, -1):
if text[i].isdigit() and re.search('[a-zA-Z]', text[start:i+1]) is None:
end = i
break
if start != -1 and start < end:
yield TemporarySpanMention(
char_start=start, char_end=end, sentence=sentence
)
def apply(self, doc: Document) -> Iterator[TemporarySpanMention]:
"""
Generate MentionSentences from a Document by parsing all of its Sentences.
:param doc: The ``Document`` to parse.
:raises TypeError: If the input doc is not of type ``Document``.
"""
if not isinstance(doc, Document):
raise TypeError(
"Input Contexts to MentionSentences.apply() must be of type Document"
)
for sentence in doc.sentences:
yield TemporarySpanMention(char_start=0,
char_end=len(sentence.text) - 1,
sentence=sentence)
def apply(self, doc):
"""
Generate MentionSentences from a Document by parsing all of its Sentences.
:param doc: The ``Document`` to parse.
:type doc: ``Document``
:raises TypeError: If the input doc is not of type ``Document``.
"""
if not isinstance(doc, Document):
raise TypeError(
"Input Contexts to MentionSentences.apply() must be of type Document"
)
for sentence in doc.sentences:
for date_mention in self.extract_dates(sentence.text):
yield TemporarySpanMention(char_start=date_mention[0],
char_end=date_mention[1] - 1,
sentence=sentence)
def apply(self, session, doc):
"""
Generate MentionSentences from a Document by parsing all of its Sentences.
:param session: The database session
:param doc: The ``Document`` to parse.
:type doc: ``Document``
:raises TypeError: If the input doc is not of type ``Document``.
"""
if not isinstance(doc, Document):
raise TypeError(
"Input Contexts to MentionSentences.apply() must be of type Document"
)
doc = session.query(Document).filter(Document.id == doc.id).one()
for sentence in doc.sentences:
yield TemporarySpanMention(
char_start=0, char_end=len(sentence.text) - 1, sentence=sentence
)