如何导航nltk.tree.tree?

如何导航nltk.tree.tree?,tree,nltk,Tree,Nltk,我用以下句子拼凑了一个句子: grammar = ''' NP:

我用以下句子拼凑了一个句子:

grammar = '''                                                                                                              
    NP:                                                                                                                    
       {<DT>*(<NN.*>|<JJ.*>)*<NN.*>}                                                                                       
     NVN:                                                                                                                  
       {<NP><VB.*><NP>}                                                                                                    
    '''
chunker = nltk.chunk.RegexpParser(grammar)
tree = chunker.parse(tagged)
print tree
但现在我被困在试图找出如何导航。我希望能够找到NVN子树,并访问左侧的名词短语(“the_Pigs”)、动词(“are”)和右侧的名词短语(“布里斯托尔朋克摇滚乐队”)。我该怎么做?

试试这个:

for a in tree:
        if type(a) is nltk.Tree:
            if a.node == 'NVN': # This climbs into your NVN tree
                for b in a:
                    if type(b) is nltk.Tree and b.node == 'NP':
                        print b.leaves() # This outputs your "NP"
                    else:
                        print b # This outputs your "VB.*"
它的输出是:

[(‘猪’,‘NNS’)]

(“are”、“VBP”)

[('a','DT'),('Bristol-based','JJ'),('punk','NN'),('rock','NN'), ('band','NN')]


当然,你可以编写自己的深度优先搜索。。。但是有一个更简单(更好)的方法。如果希望每个子树都以NVM为根,请使用树的子树方法并定义过滤器参数

>>> print t
(S
    (NVN
        (NP The_Pigs/NNS)
        are/VBP
        (NP a/DT Bristol-based/JJ punk/NN rock/NN band/NN))
    that/WDT
    formed/VBN
    in/IN
    1977/CD
    ./.)
>>> for i in t.subtrees(filter=lambda x: x.node == 'NVN'):
...     print i
... 
(NVN
    (NP The_Pigs/NNS)
    are/VBP
    (NP a/DT Bristol-based/JJ punk/NN rock/NN band/NN))
尝试:


下面是一个代码示例,用于生成带有标签“NP”的所有子树

def filt(x):
    return x.label()=='NP'

for subtree in t.subtrees(filter =  filt): # Generate all subtrees
    print subtree
对于兄弟姐妹,您可能需要查看方法
ParentedTree.left\u sibbins()

有关更多详细信息,这里有一些有用的链接

#一些基本用法和示例 #使用这些方法制作的笔记本


#所有带源代码的api

你能发布叶节点的完整语法吗,然后我可以给你一个清晰的示例?另一个DFS示例(带
ParentedTree
):是的,谢谢。请注意,NLTK的接口可能会随着时间的推移而更改。对于Python 3.5和NLTK 3.2.2,lambda函数应该使用node:filter=lambda x:x.label()=“NP”的label()属性
ROOT = 'ROOT'
tree = ...
def getNodes(parent):
    for node in parent:
        if type(node) is nltk.Tree:
            if node.label() == ROOT:
                print "======== Sentence ========="
                print "Sentence:", " ".join(node.leaves())
            else:
                print "Label:", node.label()
                print "Leaves:", node.leaves()

            getNodes(node)
        else:
            print "Word:", node

getNodes(tree)
def filt(x):
    return x.label()=='NP'

for subtree in t.subtrees(filter =  filt): # Generate all subtrees
    print subtree