stanford_corenlp_py

Stanford's Deep Learning Sentiment Analysis is the state of the art in open-source sentiment analysis as of this paper's publication.

Existing Python wrappers for Stanford's CoreNLP package use subprocess to run the Java pipeline from the command line; however, much of those code bases is around subprocess/socket management and by and large reinvents the functionality of an already mature Python/Java communication package called py4j.

This repo provides a Python interface for calling the "sentiment" and "entitymentions" annotators of Stanford's CoreNLP Java package, current as of v. 3.5.1. It uses py4j to interact with the JVM; as such, in order to run a script like scripts/runGateway.py, you must first compile and run the Java classes creating the JVM gateway.

Requirements:

1. Download the CoreNLP jars here: http://nlp.stanford.edu/software/stanford-corenlp-full-2015-01-29.zip

2. You can download py4j with pip install py4j. More info here: http://py4j.sourceforge.net/

3. Set the bash environment variables CORENLP and PY4JJAR as locations of the CoreNLP jars and py4j jar, respectively. E.g. in your .bash_profile:

export PY4JJAR=/System/Library/Frameworks/Python.framework/Versions/2.7/share/py4j/py4j0.8.2.1.jar
export CORENLP=/Users/elizachang/projects/corenlp

You may then start interacting with the Java objects and calling the methods in PipelineAnnotator and NLPEntryPoint in Python.

Running

1. To start the JVM, run from this project's home directory:

$ javac -cp .:$PY4JJAR:$CORENLP/* nlpgateway/*.java
$ java -cp .:$PY4JJAR:$CORENLP/* nlpgateway/NLPEntryPoint

1. Run/edit the example script provided:

python scripts/runGateway.py