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[英]Replacing only pronoun, noun, verb and adjective in a sentence with its corresponding tags, how could I do it efficiently in Python?
[英]How do I get the correct pos tags for a sentence after noun phrase merging?
我正在嘗試合並一個句子中的名詞短語塊,然后獲取合並文檔中每個標記的 pos 標簽。 但是,對於每個合並的跨度,我似乎獲得了跨度中第一個標記的 pos 標記(通常是 DET 或 ADJ)而不是 NOUN。
這是代碼:
def noun_chunk_retokenizer(doc):
with doc.retokenize() as retokenizer:
for chunk in doc.noun_chunks:
retokenizer.merge(chunk)
return doc
nlp = spacy.load('en_core_web_sm')
nlp.add_pipe(noun_chunk_retokenizer)
query = "when is the tennis match happening?"
[(c.text,c.pos_) for c in nlp(query)]
這是我得到的結果:
[('when', 'ADV'),
('is', 'VERB'),
('the tennis match', 'DET'),
('happening', 'VERB'),
('?', 'PUNCT')]
但我希望“網球比賽”被標記為“名詞”,這就是它在顯示演示中的工作方式: https ://explosion.ai/demos/displacy?
似乎應該有一種“標准”的方式來做到這一點,但我不確定如何。
您應該使用內置的merge_noun_chunks
組件。 請參閱 管道函數文檔:
將名詞塊合並為一個標記。 也可以通過字符串名稱
"merge_noun_chunks"
。 初始化后,通常使用nlp.add_pipe將組件添加到處理管道中。
字符串的示例用法:
import spacy
nlp = spacy.load('en_core_web_sm')
nlp.add_pipe(nlp.create_pipe('merge_noun_chunks'))
query = "when is the tennis match happening?"
[(c.text,c.pos_) for c in nlp(query)]
輸出:
[('when', 'ADV'),
('is', 'VERB'),
('the tennis match', 'NOUN'),
('happening', 'VERB'),
('?', 'PUNCT')]
至於“如何在源代碼中完成”的問題,請參閱第 7 行的spacy Github repo , /spaCy/blob/master/spacy/pipeline/functions.py
文件:
def merge_noun_chunks(doc):
"""Merge noun chunks into a single token.
doc (Doc): The Doc object.
RETURNS (Doc): The Doc object with merged noun chunks.
DOCS: https://spacy.io/api/pipeline-functions#merge_noun_chunks
"""
if not doc.is_parsed:
return doc
with doc.retokenize() as retokenizer:
for np in doc.noun_chunks:
attrs = {"tag": np.root.tag, "dep": np.root.dep}
retokenizer.merge(np, attrs=attrs)
return doc
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