SpaCy Matcher 未返回匹配项

问题描述

import spacy
from spacy.matcher import Matcher
nlp = spacy.load("en_core_web_sm")

matcher = Matcher(nlp.vocab,validate=True)

patterns = [{"LOWER": "self"},{"LOWER": "employed"},{"OP": "?"},{"LOWER": "average"}]
    
matcher.add("Category 1",None,patterns)
    
doc = nlp(u"I am a self employed working in a remote factory. I have a flat located in NYC,but I want to sell it to change for a new one. This new flat is situated in Connecticut,facing a nice lake.  This flat Could be sold for 0.5 million dollars. That is an average price in the neighborhood")
matches = matcher(doc)
for match_id,start,end in matches:
        rule_id = nlp.vocab.strings[match_id]  # get the unicode ID,i.e. 'CategoryID'
        span = doc[start : end]  # get the matched slice of the doc
        print(rule_id,span.text)

它不返回任何匹配项。我希望看到的是

# Category 1 self employed average

我创建了这个假句子来提取“自雇”和“平均”。事实上，我们不知道这句话的样子。

我的目的是提取 'self-resident' 和 'average'，不管它们在哪里，什么词的顺序是什么（例如，average 是在 self-dependent 之前）。

如何处理？感谢您的任何反馈

解决方法

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matcher nlp python