Python Spacy DependencyMatcher返回空值
教程中的代码: 结果我应该得到[(485136312962674176[6,0,10,9])] 我得到的是这个[] 我的环境Python Spacy DependencyMatcher返回空值,python,machine-learning,nlp,spacy,Python,Machine Learning,Nlp,Spacy,教程中的代码: 结果我应该得到[(485136312962674176[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 您正在使用ORTH查找“已建立”。这是区分大小写的。您应该将ORTH替换为LOWER,或者在输入语句中使用小写字母谢谢您,克里斯! import spacy import en_core_web_sm from spacy.matcher i
- spaCy版本:3.0.5
- 平台:Windows-10
- Python版本:3.6.13
- en_core_web_sm=3.0.0
- 您正在使用ORTH查找“已建立”。这是区分大小写的。您应该将ORTH替换为LOWER,或者在输入语句中使用小写字母谢谢您,克里斯!
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)