mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 02:16:32 +03:00
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
"""Example of adding a pipeline component to prohibit sentence boundaries
|
|
before certain tokens.
|
|
|
|
What we do is write to the token.is_sent_start attribute, which
|
|
takes values in {True, False, None}. The default value None allows the parser
|
|
to predict sentence segments. The value False prohibits the parser from inserting
|
|
a sentence boundary before that token. Note that fixing the sentence segmentation
|
|
should also improve the parse quality.
|
|
|
|
The specific example here is drawn from https://github.com/explosion/spaCy/issues/2627
|
|
Other versions of the model may not make the original mistake, so the specific
|
|
example might not be apt for future versions.
|
|
"""
|
|
import plac
|
|
import spacy
|
|
|
|
|
|
def prevent_sentence_boundaries(doc):
|
|
for token in doc:
|
|
if not can_be_sentence_start(token):
|
|
token.is_sent_start = False
|
|
return doc
|
|
|
|
|
|
def can_be_sentence_start(token):
|
|
if token.i == 0:
|
|
return True
|
|
elif token.is_title:
|
|
return True
|
|
elif token.nbor(-1).is_punct:
|
|
return True
|
|
elif token.nbor(-1).is_space:
|
|
return True
|
|
else:
|
|
return False
|
|
|
|
|
|
def main():
|
|
nlp = spacy.load("en_core_web_lg")
|
|
raw_text = "Been here and I'm loving it."
|
|
doc = nlp(raw_text)
|
|
sentences = [sent.string.strip() for sent in doc.sents]
|
|
print(sentences)
|
|
nlp.add_pipe(prevent_sentence_boundaries, before="parser")
|
|
doc = nlp(raw_text)
|
|
sentences = [sent.string.strip() for sent in doc.sents]
|
|
print(sentences)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
plac.call(main)
|