如何漂亮地打印nltk树对象?

如果您正在寻找一个带括号的解析输出,那么可以使用 Tree.pprint()

>>> import nltk 
>>> sentence = [("the", "DT"), ("little", "JJ"), ("yellow", "JJ"), ("dog", "NN"), ("barked","VBD"), ("at", "IN"), ("the", "DT"), ("cat", "NN")]
>>> 
>>> pattern = """NP: {<DT>?<JJ>*<NN>}
... VBD: {<VBD>}
... IN: {<IN>}"""
>>> NPChunker = nltk.RegexpParser(pattern) 
>>> result = NPChunker.parse(sentence)
>>> result.pprint()
(S
  (NP the/DT little/JJ yellow/JJ dog/NN)
  (VBD barked/VBD)
  (IN at/IN)
  (NP the/DT cat/NN))

但很可能你在找

                             S                                      
            _________________|_____________________________          
           NP                        VBD       IN          NP       
   ________|_________________         |        |      _____|____     
the/DT little/JJ yellow/JJ dog/NN barked/VBD at/IN the/DT     cat/NN

Tree.pretty_print() https://github.com/nltk/nltk/blob/develop/nltk/tree.py#L692 :

def pretty_print(self, sentence=None, highlight=(), stream=None, **kwargs):
    """
    Pretty-print this tree as ASCII or Unicode art.
    For explanation of the arguments, see the documentation for
    `nltk.treeprettyprinter.TreePrettyPrinter`.
    """
    from nltk.treeprettyprinter import TreePrettyPrinter
    print(TreePrettyPrinter(self, sentence, highlight).text(**kwargs),
          file=stream)

它创造了一个 TreePrettyPrinter 对象, https://github.com/nltk/nltk/blob/develop/nltk/treeprettyprinter.py#L50

class TreePrettyPrinter(object):
    def __init__(self, tree, sentence=None, highlight=()):
        if sentence is None:
            leaves = tree.leaves()
            if (leaves and not any(len(a) == 0 for a in tree.subtrees())
                    and all(isinstance(a, int) for a in leaves)):
                sentence = [str(a) for a in leaves]
            else:
                # this deals with empty nodes (frontier non-terminals)
                # and multiple/mixed terminals under non-terminals.
                tree = tree.copy(True)
                sentence = []
                for a in tree.subtrees():
                    if len(a) == 0:
                        a.append(len(sentence))
                        sentence.append(None)
                    elif any(not isinstance(b, Tree) for b in a):
                        for n, b in enumerate(a):
                            if not isinstance(b, Tree):
                                a[n] = len(sentence)
                                sentence.append('%s' % b)
        self.nodes, self.coords, self.edges, self.highlight = self.nodecoords(
                tree, sentence, highlight)

sentence.append('%s' % b) https://github.com/nltk/nltk/blob/develop/nltk/treeprettyprinter.py#L97

问题是 为什么会引起打字错误

TypeError: not all arguments converted during string formatting

如果我们仔细看,它看起来让我们可以使用 print('%s' % b)

# String
>>> x = 'abc'
>>> type(x)
<class 'str'>
>>> print('%s' % x)
abc

# Integer
>>> x = 123
>>> type(x)
<class 'int'>
>>> print('%s' % x)
123

# Float 
>>> x = 1.23
>>> type(x)
<class 'float'>
>>> print('%s' % x)
1.23

# Boolean
>>> x = True
>>> type(x)
<class 'bool'>
>>> print('%s' % x)
True

令人惊讶的是,它甚至可以在列表中使用!

>>> x = ['abc', 'def']
>>> type(x)
<class 'list'>
>>> print('%s' % x)
['abc', 'def']

但它被 tuple !!

>>> x = ('DT', 123)
>>> x = ('abc', 'def')
>>> type(x)
<class 'tuple'>
>>> print('%s' % x)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: not all arguments converted during string formatting

所以如果我们回到 https://github.com/nltk/nltk/blob/develop/nltk/treeprettyprinter.py#L95

if not isinstance(b, Tree):
    a[n] = len(sentence)
    sentence.append('%s' % b)

既然我们知道 句子.append(“%s”%b) 无法处理 ,添加对元组类型的检查并以某种方式连接元组中的项并转换为 str 将产生美好的 pretty_print :

if not isinstance(b, Tree):
    a[n] = len(sentence)
    if type(b) == tuple:
        b = '/'.join(b)
    sentence.append('%s' % b)

S码
_________________|_____________________________
NP中的NP-VBD
________|_________________         |        |      _____|____

而不改变 nltk

让我们看看 result i、 东阿 Tree

Tree('S', [Tree('NP', [('the', 'DT'), ('little', 'JJ'), ('yellow', 'JJ'), ('dog', 'NN')]), Tree('VBD', [('barked', 'VBD')]), Tree('IN', [('at', 'IN')]), Tree('NP', [('the', 'DT'), ('cat', 'NN')])])

看起来叶子是作为字符串的元组列表保存的。 [('the', 'DT'), ('cat', 'NN')] ,所以我们可以做一些黑客,使它成为字符串列表,例如。 [('the/DT'), ('cat/NN')] Tree.pretty\u打印() 会玩得很好。

既然我们知道 树.pprint()

(S
  (NP the/DT little/JJ yellow/JJ dog/NN)
  (VBD barked/VBD)
  (IN at/IN)
  (NP the/DT cat/NN))

我们可以简单地输出一个带括号的解析字符串,然后重新读取解析 树 Tree.fromstring() :

from nltk import Tree
Tree.fromstring(str(result)).pretty_print()

最终付款:

import nltk 
sentence = [("the", "DT"), ("little", "JJ"), ("yellow", "JJ"), ("dog", "NN"), ("barked","VBD"), ("at", "IN"), ("the", "DT"), ("cat", "NN")]

pattern = """NP: {<DT>?<JJ>*<NN>}
VBD: {<VBD>}
IN: {<IN>}"""
NPChunker = nltk.RegexpParser(pattern) 
result = NPChunker.parse(sentence)

Tree.fromstring(str(result)).pretty_print()

[输出]:

S码
NP中的NP-VBD
________|_________________         |        |      _____|____