为nltk解析树生成语法规则

Question

如果我有句子"Mary saw a dog"和以下内容：

pos_tags = ['NNP', 'VBD', 'DT', 'NN']

是否可以为这个句子生成语法规则，以便生成一个解析树（下面的语法是使用nltk.parse_cfg的语法规则）

sent = "Mary saw a dog".split()
rd_parser = nltk.RecursiveDescentParser(grammar)

for tree in rd_parser.nbest_parse(sent):
    print tree

Answer 1

您可以尝试：

import nltk
# Define the cfg grammar.
grammar = nltk.parse_cfg("""
S -> NP VP
NP -> 'DT' 'NN'
VP -> 'VB'
VP -> 'VB' 'NN'
""")


# Make your POS sentence into a list of tokens.
sentence = "DT NN VB NN".split(" ")

# Load the grammar into the ChartParser.
cp = nltk.ChartParser(grammar)

# Generate and print the nbest_parse from the grammar given the sentence tokens.
for tree in cp.nbest_parse(sentence):
    print tree

但是，正如@alexis所强调的那样，你要求的东西是不可能的=）