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Linguistic Typology

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Volume 20, Issue 3


Linguistic typology in natural language processing

Emily M. Bender
  • Department of Linguistics, University of Washington, Guggenheim Hall, 4th Floor, Box 352425, Seattle, WA 98195, U.S.A.
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Published Online: 2016-12-23 | DOI: https://doi.org/10.1515/lingty-2016-0035


This paper explores the ways in which the field of natural language processing (NLP) can and does benefit from work in linguistic typology. I describe the recent increase in interest in multilingual natural language processing and give a high-level overview of the field. I then turn to a discussion of how linguistic knowledge in general is incorporated in NLP technology before describing how typological results in particular are used. I consider both rule-based and machine learning approaches to NLP and review literature on predicting typological features as well as that which leverages such features.


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About the article

Received: 2016-08-03

Revised: 2016-09-06

Published Online: 2016-12-23

Published in Print: 2016-12-01

Citation Information: Linguistic Typology, Volume 20, Issue 3, Pages 645–660, ISSN (Online) 1613-415X, ISSN (Print) 1430-0532, DOI: https://doi.org/10.1515/lingty-2016-0035.

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