Coreference resolution in python nltk using Stanford coreNLP
<p>Stanford CoreNLP provides coreference resolution <a href="http://nlp.stanford.edu/software/dcoref.shtml" rel="nofollow">as mentioned here</a>, also <a href="http://stackoverflow.com/questions/30954649/coreference-resolution-using-stanford-corenlp">this thread</a>, <a href="http://stackoverflow.com/questions/30362691/stanford-corenlp-wrong-coreference-resolution">this</a>,   provides some insights about its implementation in Java.</p>

<p>However, I am using python and NLTK and I am not sure how can I use Coreference resolution functionality of CoreNLP in my python code. I have been able to set up StanfordParser in NLTK, this is my code so far.</p>

<pre><code>from nltk.parse.stanford import StanfordDependencyParser
stanford_parser_dir = 'stanford-parser/'
eng_model_path = stanford_parser_dir  + "stanford-parser-models/edu/stanford/nlp/models/lexparser/englishRNN.ser.gz"
my_path_to_models_jar = stanford_parser_dir  + "stanford-parser-3.5.2-models.jar"
my_path_to_jar = stanford_parser_dir  + "stanford-parser.jar"
</code></pre>

<p>How can I use coreference resolution of CoreNLP in python?</p>

<p>Maybe this works for you? <a href="https://github.com/dasmith/stanford-corenlp-python" rel="nofollow">https://github.com/dasmith/stanford-corenlp-python</a>
If not, you can try to combine the two yourself using <a href="http://www.jython.org/" rel="nofollow">http://www.jython.org/</a></p>

python nlp nltk stanford-nlp