A categorial variation database for English

Nizar Habash; Bonnie Dorr

A categorial variation database for English

Computer Science

Research output: Contribution to conference › Paper › peer-review

Abstract

We describe our approach to the construction and evaluation of a large-scale database called “CatVar” which contains categorial variations of English lexemes. Due to the prevalence of cross-language categorial variation in multilingual applications, our categorial-variation resource may serve as an integral part of a diverse range of natural language applications. Thus, the research reported herein overlaps heavily with that of the machine-translation, lexicon-construction, and information-retrieval communities. We apply the information-retrieval metrics of precision and recall to evaluate the accuracy and coverage of our database with respect to a human-produced gold standard. This evaluation reveals that the categorial database achieves a high degree of precision and recall. Additionally, we demonstrate that the database improves on the linkability of Porter stemmer by over 30%.

Original language	English (US)
State	Published - 2003
Event	2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003 - Edmonton, Canada Duration: May 27 2003 → Jun 1 2003

Conference

Conference	2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003
Country/Territory	Canada
City	Edmonton
Period	5/27/03 → 6/1/03

ASJC Scopus subject areas

Language and Linguistics
Linguistics and Language

Cite this

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title = "A categorial variation database for English",

abstract = "We describe our approach to the construction and evaluation of a large-scale database called “CatVar” which contains categorial variations of English lexemes. Due to the prevalence of cross-language categorial variation in multilingual applications, our categorial-variation resource may serve as an integral part of a diverse range of natural language applications. Thus, the research reported herein overlaps heavily with that of the machine-translation, lexicon-construction, and information-retrieval communities. We apply the information-retrieval metrics of precision and recall to evaluate the accuracy and coverage of our database with respect to a human-produced gold standard. This evaluation reveals that the categorial database achieves a high degree of precision and recall. Additionally, we demonstrate that the database improves on the linkability of Porter stemmer by over 30%.",

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AU - Habash, Nizar

AU - Dorr, Bonnie

N1 - Publisher Copyright: © 2003 Proceedings of the 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, HLT-NAACL 2003. All rights reserved.

PY - 2003

Y1 - 2003

N2 - We describe our approach to the construction and evaluation of a large-scale database called “CatVar” which contains categorial variations of English lexemes. Due to the prevalence of cross-language categorial variation in multilingual applications, our categorial-variation resource may serve as an integral part of a diverse range of natural language applications. Thus, the research reported herein overlaps heavily with that of the machine-translation, lexicon-construction, and information-retrieval communities. We apply the information-retrieval metrics of precision and recall to evaluate the accuracy and coverage of our database with respect to a human-produced gold standard. This evaluation reveals that the categorial database achieves a high degree of precision and recall. Additionally, we demonstrate that the database improves on the linkability of Porter stemmer by over 30%.

AB - We describe our approach to the construction and evaluation of a large-scale database called “CatVar” which contains categorial variations of English lexemes. Due to the prevalence of cross-language categorial variation in multilingual applications, our categorial-variation resource may serve as an integral part of a diverse range of natural language applications. Thus, the research reported herein overlaps heavily with that of the machine-translation, lexicon-construction, and information-retrieval communities. We apply the information-retrieval metrics of precision and recall to evaluate the accuracy and coverage of our database with respect to a human-produced gold standard. This evaluation reveals that the categorial database achieves a high degree of precision and recall. Additionally, we demonstrate that the database improves on the linkability of Porter stemmer by over 30%.

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A categorial variation database for English

Abstract

Conference

ASJC Scopus subject areas

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