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Ckyish NLTK parsing

This branch experiments with adding rules to the chart parser. Currently there are additions that with this strategy

leaf_init = nltk.parse.chart.LeafInitRule()
bottom_up_predict = nltk.parse.chart.BottomUpPredictRule()
double_edge = nltk.parse.chart.DoubleEdgeFundamentalRule()
lexical_single_edge = nltk.parse.chart.LexicalSingleEdgeFundamentalRule()

strategy = [leaf_init,
            lexical_single_edge,
            bottom_up_predict,
            double_edge]

emulate CKY parsing. See notebooks/ckyish.ipynb for an illustration with the stepping chart parser.

Natural Language Toolkit (NLTK)

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NLTK -- the Natural Language Toolkit -- is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. NLTK requires Python version 3.5, 3.6, 3.7, or 3.8.

For documentation, please visit nltk.org.

Contributing

Do you want to contribute to NLTK development? Great! Please read CONTRIBUTING.md for more details.

See also how to contribute to NLTK.

Donate

Have you found the toolkit helpful? Please support NLTK development by donating to the project via PayPal, using the link on the NLTK homepage.

Citing

If you publish work that uses NLTK, please cite the NLTK book, as follows:

Bird, Steven, Edward Loper and Ewan Klein (2009).
Natural Language Processing with Python.  O'Reilly Media Inc.

Copyright

Copyright (C) 2001-2020 NLTK Project

For license information, see LICENSE.txt.

AUTHORS.md contains a list of everyone who has contributed to NLTK.

Redistributing

  • NLTK source code is distributed under the Apache 2.0 License.
  • NLTK documentation is distributed under the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States license.
  • NLTK corpora are provided under the terms given in the README file for each corpus; all are redistributable and available for non-commercial use.
  • NLTK may be freely redistributed, subject to the provisions of these licenses.

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