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emilymbender edited this page Jun 30, 2023 · 45 revisions

Page Authorship

This page is written and maintained by EmilyBender. Please send comments by email.

Overview

The LinGO Grammar Matrix is an open-source starter-kit for rapid prototyping of precision broad-coverage grammars compatible with the LKB. The Matrix thrives on input from users working on varied languages. If you're interested, please contact us --- through the mailing list, or by emailing Emily Bender at ebender at u dot washington dot edu.

The Wish List page serves as a forum for relatively informal exchange among developers and consumers, in addition to the Matrix mailing list.

There is an excellent guide available (Flickinger, Dan, Emily M. Bender and Stephan Oepen. 2003. MRS in the LinGO Grammar Matrix: A Practical User's Guide. ms). Some of it is out of date, but it is still the best single source of information.

Details

Courses

Grammars

The Grammar Matrix has been used as the basis for the following grammars:

  • The NorSource Grammar (Hellan and Haugereid, 2003)

  • KRG: The Korean Resource Grammar (Kim and Yang, 2003)

  • The Modern Greek Grammar (Kordoni and Neu, 2005)

  • The Spanish Resource Grammar (Marimon, Bel and Seghezzi, 2007)

  • LXGram: Portuguese Grammar (Branco and Costa, 2008)

  • HaG (Hausa Grammar; Crysmann, 2009)

  • BURGER Bulgarian

  • WambayaTop: wmb (Wambaya; Bender, 2008)

  • MCG Mandarin

  • ManGO Mandarin

Current events

  • 8/11/11: Customization system source code available

  • 10/27/08: New trac site announced. Submit bug reports here! Update: trac was getting spammed. Please submit bug reports (with choices files, if appropriate) to matrix-dev -at- uw.edu.

  • We are currently expanding the phenomenon libraries to include case, agreement, tense and aspect, as well as extensions to the existing libraries for word order, sentential negation, yes-no questions and coordination.

  • PET now has :+.

  • MatrixDevTop: Notes for Matrix developers

Acknowledgments

Work on the Grammar Matrix is currently supported by an NSF CAREER grant (BCS-0644097).

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