如何用spaCy获取依赖树？

我一直在尝试寻找如何使用 spaCy 获取依赖树，但我找不到任何有关如何获取树的信息，只能在如何导航树 https://spacy.io/usage/examples#subtrees.

如果有人想轻松查看 spacy 生成的依赖关系树，一种解决方案是将其转换为nltk.tree.Tree http://www.nltk.org/api/nltk.html#nltk.tree.Tree并使用nltk.tree.Tree.pretty_print http://www.nltk.org/api/nltk.html#nltk.tree.Tree.pretty_print方法。这是一个例子：

import spacy
from nltk import Tree


en_nlp = spacy.load('en')

doc = en_nlp("The quick brown fox jumps over the lazy dog.")

def to_nltk_tree(node):
    if node.n_lefts + node.n_rights > 0:
        return Tree(node.orth_, [to_nltk_tree(child) for child in node.children])
    else:
        return node.orth_


[to_nltk_tree(sent.root).pretty_print() for sent in doc.sents]

Output:

                jumps                  
  ________________|____________         
 |    |     |     |    |      over     
 |    |     |     |    |       |        
 |    |     |     |    |      dog      
 |    |     |     |    |    ___|____    
The quick brown  fox   .  the      lazy

Edit:要更改令牌表示，您可以执行以下操作：

def tok_format(tok):
    return "_".join([tok.orth_, tok.tag_])


def to_nltk_tree(node):
    if node.n_lefts + node.n_rights > 0:
        return Tree(tok_format(node), [to_nltk_tree(child) for child in node.children])
    else:
        return tok_format(node)

结果是：

                         jumps_VBZ                           
   __________________________|___________________             
  |       |        |         |      |         over_IN        
  |       |        |         |      |            |            
  |       |        |         |      |          dog_NN        
  |       |        |         |      |     _______|_______     
The_DT quick_JJ brown_JJ   fox_NN  ._. the_DT         lazy_JJ