Welcome to CoreNLP XML Library’s documentation!

This library is designed to add a data model over Stanford CoreNLP’s basic XML output.

The Document class is designed to provide lazy-loaded access to information from syntax, coreference, and dependency parse structures within the XML.

Installing the Library

It’s as easy as

pip install corenlp_xml

What You Can Do With This Library

Some code examples:

from corenlp_xml import Document

doc = Document(xml_string)

# The first sentence
s1 = doc.sentences[0]

# Noun phrases for the first sentence
s1_nps = s1.phrase_strings("np")

# Text of semantic head of first sentence
s1_head = s1.semantic_head.text

# Find all representative coreferences matching noun phrases in sentence 1
s1_corefs = [coref for coref in doc.coreferences
             if coref.representative and coref.sentence == s1]


Indices and tables