From the README.md:
This is 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 a JSON-RPC server. Because it uses many large trained models (requiring 3GB RAM on 64-bit machines and usually a few minutes loading time), most applications will probably want to run it as a server.
- Python interface to Stanford CoreNLP tools: tagging, phrase-structure parsing, dependency parsing, named entity resolution, and coreference resolution.
- Runs an JSON-RPC server that wraps the Java server and outputs JSON.
- Outputs parse trees which can be used by nltk.
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, but it has been tested on Core NLP tools version 1.3.3 released 2012-07-09.
If you have NLP requirements and work in Python, this may be of interest.