Catherine Havasi


2021

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RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations
Pedro Colon-Hernandez | Yida Xin | Henry Lieberman | Catherine Havasi | Cynthia Breazeal | Peter Chin
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

2015

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Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Matt Gerber | Catherine Havasi | Finley Lacatusu
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations

2012

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Representing General Relational Knowledge in ConceptNet 5
Robyn Speer | Catherine Havasi
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

ConceptNet is a knowledge representation project, providing a large semantic graph that describes general human knowledge and how it is expressed in natural language. This paper presents the latest iteration, ConceptNet 5, including its fundamental design decisions, ways to use it, and evaluations of its coverage and accuracy.

2006

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Classification of Discourse Coherence Relations: An Exploratory Study using Multiple Knowledge Sources
Ben Wellner | James Pustejovsky | Catherine Havasi | Anna Rumshisky | Roser Saurí
Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue

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BULB: A Unified Lexical Browser
Catherine Havasi | James Pustejovsky | Marc Verhagen
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Natural language processing researchers currently have access to a wealth of information about words and word senses. This presents problems as well as resources, as it is often difficult to search through and coordinate lexical information across various data sources. We have approached this problem by creating a shared environment for various lexical resources. This browser, BULB (Brandeis Unified Lexical Browser) and its accompanying front-end provides the NLP researcher with a coordinated display from many of the available lexical resources, focusing, in particular, on a newly developed lexical database, the Brandeis Semantic Ontology (BSO). BULB is a module-based browser focusing on the interaction and display of modules from existing NLP tools. We discuss the BSO, PropBank, FrameNet, WordNet, and CQP, as well as other modules which will extend the system. We then outline future extensions to this work and present a release schedule for BULB.

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Towards a Generative Lexical Resource: The Brandeis Semantic Ontology
James Pustejovsky | Catherine Havasi | Jessica Littman | Anna Rumshisky | Marc Verhagen
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

In this paper we describe the structure and development of the Brandeis Semantic Ontology (BSO), a large generative lexicon ontology and lexical database. The BSO has been designed to allow for more widespread access to Generative Lexicon-based lexical resources and help researchers in a variety of computational tasks. The specification of the type system used in the BSO largely follows that proposed by the SIMPLE specification (Busa et al., 2001), which was adopted by the EU-sponsored SIMPLE project (Lenci et al., 2000).