python - 如何在negspacy中提取特定单词

Question

当我将 negspacy 应用于我的句子时，我希望 negspacy 将特定短语视为单个实体并为其提供输出。

import en_core_sci_lg
from negspacy.negation import Negex
nlp = en_core_sci_lg.load()

negex = Negex(nlp, language = "en_clinical_sensitive")
nlp.add_pipe(negex, last=True)

doc = nlp(""" patient has no signs of shortness of breath. """)

for word in doc.ents:
    print(word, word._.negex)

输出是 -

patient False
shortness True

我希望输出是 -

patient False
shortness of breath True

我如何将“呼吸急促”、“喉咙痛”、“呼吸窘迫”等短语视为一个整体。
我试过了 -

import en_core_sci_lg
from negspacy.negation import Negex
nlp = en_core_sci_lg.load()
from spacy.pipeline import EntityRuler
ruler = EntityRuler(nlp)
patterns =  [{"label": "ENTITY", "pattern": [{"LOWER": "shortness"}, {"LOWER": "of"}, {"LOWER": "breath"}]}]

ruler.add_patterns(patterns)
nlp.add_pipe(ruler)
negex = Negex(nlp, language = "en_clinical")
nlp.add_pipe(negex, last=True)

doc = nlp("""patient has no signs of shortness of breath. """)

for word in doc.ents:
    print(word, word._.negex)

输出还在后面——

patient False
shortness True

我能做些什么来解决这个问题

Answer 1

您可能很高兴知道解决您的问题的方法非常简单。您只是缺少关键字参数 overwrite_ents=True在 EntityRuler构造函数，因此您添加的自定义模式正在被其他实体覆盖。只是改变:

ruler = EntityRuler(nlp)

到

ruler = EntityRuler(nlp, overwrite_ents=True)

现在，我的输出是:

patient False
shortness of breath True