小编kar*_*ddy的帖子

我尝试使用 spacy 从文本中提取所需的自定义实体。

import spacy
from spacy_lookup import Entity
data = {0:["count"],1:["unique count","unique"]}

def processText(text):
    nlp = spacy.blank('en')
    for i,arr in data.items():
        fLabel = "test:"+str(i)
        fEntitty = Entity(keywords_list=list(set(arr)),label=fLabel)
        fEntitty.name = fLabel
        nlp.add_pipe(fEntitty)
    match_doc = nlp(text)
    print(match_doc.ents)
processText("unique count of city")

但上面的代码抛出了类似的错误

ValueError: [E103] Trying to set conflicting doc.ents: '(1, 2, 'test:0')' and '(0, 2, 'test:1')'. A token can only be part of one entity, so make sure the entities you're setting don't overlap.

不仅是这个案例，还有同样的人名问题，比如 Karthik vs Karthik reddy、Jon vs Jon …