将依赖解析的输出转换为树

Question

我正在使用 Stanford dependency parser 并且我得到了句子的以下输出

I shot an elephant in my sleep

python dep_parsing.py 
[((u'shot', u'VBD'), u'nsubj', (u'I', u'PRP')), ((u'shot', u'VBD'), u'dobj', (u'elephant', u'NN')), ((u'elephant', u'NN'), u'det', (u'an', u'DT')), ((u'shot', u'VBD'), u'nmod', (u'sleep', u'NN')), ((u'sleep', u'NN'), u'case', (u'in', u'IN')), ((u'sleep', u'NN'), u'nmod:poss', (u'my', u'PRP$'))]

我想把它转换成一个图，节点是每个标记，边是它们之间的关系。

我需要图形结构进行进一步处理，因此如果对其进行修改很容易并且必须易于表示，那将会有所帮助。

这是我到目前为止的代码。

from nltk.parse.stanford import StanfordDependencyParser
stanford_parser_dir = 'stanford-parser/'
eng_model_path = stanford_parser_dir  + "stanford-parser-models/edu/stanford/nlp/models/lexparser/englishRNN.ser.gz"
my_path_to_models_jar = stanford_parser_dir  + "stanford-parser-3.5.2-models.jar"
my_path_to_jar = stanford_parser_dir  + "stanford-parser.jar"

dependency_parser = StanfordDependencyParser(path_to_jar=my_path_to_jar, path_to_models_jar=my_path_to_models_jar)

result = dependency_parser.raw_parse('I shot an elephant in my sleep')
dep = result.next()
a = list(dep.triples())
print a

如何制作这样的图结构？

Answer 1

您可以遍历 dep.triples() 并获得您想要的输出。

代码：

for triple in dep.triples():
    print triple[1],"(",triple[0][0],", ",triple[2][0],")"

输出：

nsubj ( shot ,  I )
dobj ( shot ,  elephant )
det ( elephant ,  an )
nmod ( shot ,  sleep )
case ( sleep ,  in )
nmod:poss ( sleep ,  my )

有关更多信息，您可以查看：NLTK Dependencygraph 方法 triples()、to_dot() 和 dep.tree().draw()

编辑 -

dep.to_dot()的输出是

digraph G{
edge [dir=forward]
node [shape=plaintext]

0 [label="0 (None)"]
0 -> 2 [label="root"]
1 [label="1 (I)"]
2 [label="2 (shot)"]
2 -> 4 [label="dobj"]
2 -> 7 [label="nmod"]
2 -> 1 [label="nsubj"]
3 [label="3 (an)"]
4 [label="4 (elephant)"]
4 -> 3 [label="det"]
5 [label="5 (in)"]
6 [label="6 (my)"]
7 [label="7 (sleep)"]
7 -> 5 [label="case"]
7 -> 6 [label="nmod:poss"]
}

将依赖解析的输出转换为树

Converting output of dependency parsing to tree

python

data-structures

nlp

dependency-parsing