Work

A categorial variation database for English

Year: 2003

Type: conference-paper

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%.

Source: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)

DOI: 10.3115/1073445.1073458

Authors: Nizar Habash, Bonnie Dorr

Institution: University of Maryland, College Park

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: National Science Foundation, Directorate for Computer and Information Science and Engineering, Multidisciplinary University Research Initiative, Office of Naval Research

Awards: G2802903451, CISE Research Resources: Infrastructure to Develop a Large Scale Experiment Testbed of Multi-modal Resources