如何在python中使用斯坦福依赖解析器

Question

How to use Stanford Dependency parser in NLTK I have tired the below code It is not giving any tree structure. Can please guide, I am new to python and NLTK.

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    import os
    sentence = "this is a foo bar i want to parse."

    os.popen("echo '"+sentence+"' > ~/stanfordtemp.txt")
    parser_out = os.popen("~/stanford-parser-full-2014-06-16/lexparser.sh ~/stanfordtemp.txt").readlines()

    bracketed_parse = " ".join( [i.strip() for i in parser_out if (len(i.strip()) > 0) == "("] )
    print bracketed_parse

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Output:
Loading parser from serialized file edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz ... done [1.3 sec].
Parsing file: /home/stanfordtemp.txt
Parsing [sent. 1 len. 10]: this is a foo bar i want to parse .
Parsed file: /home/stanfordtemp.txt [1 sentences].
Parsed 10 words in 1 sentences (18.05 wds/sec; 1.81 sents/sec).

Answer 1

Have you tried one of the python wrappers listed on the Stanford NLP page? Komatsu and Castner appear to be up to v3.3 (current version is 3.4).