Spacy DependencyMatcher 返回空值

Question

教程中的代码：https://spacy.io/usage/rule-based-matching#dependencymatcher

import spacy
import en_core_web_sm
from spacy.matcher import DependencyMatcher
nlp = en_core_web_sm.load()


matcher = DependencyMatcher(nlp.vocab)

pattern = [
    {
        "RIGHT_ID": "anchor_founded",
        "RIGHT_ATTRS": {"ORTH": "founded"}
    },
    {
        "LEFT_ID": "anchor_founded",
        "REL_OP": ">",
        "RIGHT_ID": "founded_subject",
        "RIGHT_ATTRS": {"DEP": "nsubj"},
    },
    {
        "LEFT_ID": "anchor_founded",
        "REL_OP": ">",
        "RIGHT_ID": "founded_object",
        "RIGHT_ATTRS": {"DEP": "dobj"},
    },
    {
        "LEFT_ID": "founded_object",
        "REL_OP": ">",
        "RIGHT_ID": "founded_object_modifier",
        "RIGHT_ATTRS": {"DEP": {"IN": ["amod", "compound"]}},
    }
]

matcher.add("FOUNDED", [pattern])
doc = nlp("Lee, an experienced CEO, has FOUNDED two AI startups.")
matches = matcher(doc)

print(matches)

我应该得到的结果 [(4851363122962674176, [6, 0, 10, 9])] 我得到的是这个 []

我的环境

spaCy 版本：3.0.5
平台：Windows-10
Python版本：3.6.13
en_core_web_sm = 3.0.0

Answer 1

您正在使用 ORTH 查找“founded”。这是区分大小写的。您应该将 ORTH 替换为 LOWER，或者在您输入的句子中将 FOUNDED 简单地小写

Spacy DependencyMatcher 返回空值

Spacy DependencyMatcher returning empty value

python

nlp

machine-learning

spacy