1. Hiroyoshi Komatsu
  2. corenlp-python


corenlp-python / README.md

Python interface to Stanford Core NLP tools

This a Python wrapper for Stanford University's NLP group's Java-based CoreNLP tools. It can either be imported as a module or run as an JSON-RPC server. Because it uses many large trained models (requiring 3GB RAM and usually a few minutes loading time), most applications will probably want to run it as a server.

It requires pexpect. Included dependencies are jsonrpc and python-progressbar.

There's not much to this script. I decided to create it after having trouble initializing a JVM using JPypes on two different machines.

It runs the Stanford CoreNLP jar in a separate process, communicates with the java process using its command-line interface, and makes assumptions about the output of the parser in order to parse it into a Python dict object and transfer it using JSON. The parser will break if the output changes significantly. I have only tested this on Core NLP tools version 1.0.2 released 2010-11-12.

Download and Usage

You should have downloaded and unpacked the tgz file containing Stanford's CoreNLP package. Then copy all of the python files from this repository into the stanford-corenlp-2010-11-12 folder.

In other words:

sudo pip install pexpect
wget http://nlp.stanford.edu/software/stanford-corenlp-v1.0.2.tgz
tar xvfz stanford-corenlp-v1.0.2.tgz
cd stanford-corenlp-2010-11-12
git clone git://github.com/dasmith/stanford-corenlp-python.git
mv stanford-corenlp-python/* .

Then, to launch a server:

python server.py

Optionally, you can specify a host or port:

python server.py -H -p 3456

That will run a public JSON-RPC server on port 3456.

Assuming you are running on port 8080, the code in client.py shows an example parse:

import jsonrpc
server = jsonrpc.ServerProxy(jsonrpc.JsonRpc20(),
        jsonrpc.TransportTcpIp(addr=("", 8080)))

result = server.parse("hello world")
print "Result", result

Produces a list with a parsed dictionary for each sentence:

Result [{"text": "hello world", 
        "tuples": [["amod", "world", "hello"]], 
        "words": {"world": {"NamedEntityTag": "O", 
                            "CharacterOffsetEnd": "11", 
                            "Lemma": "world", 
                            "PartOfSpeech": "NN", 
                            "CharacterOffsetBegin": "6"}, 
                  "hello": {"NamedEntityTag": "O", 
                            "CharacterOffsetEnd": "5", 
                            "Lemma": "hello", 
                            "PartOfSpeech": "JJ", 
                            "CharacterOffsetBegin": "0"}}}]


Adding WordNet

Download WordNet-3.0 Prolog: http://wordnetcode.princeton.edu/3.0/WNprolog-3.0.tar.gz -->


If you think there may be a problem with this wrapper, first ensure you can run the Java program:

java -cp stanford-corenlp-2010-11-12.jar:stanford-corenlp-models-2010-11-06.jar:xom-1.2.6.jar:xom.jar:jgraph.jar:jgrapht.jar -Xmx3g edu.stanford.nlp.pipeline.StanfordCoreNLP -props default.properties