Python Spacy DependencyMatcher返回空值

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

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 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)