This paper presents a universal morphological feature schema that represents the finest distinctions in meaning that are expressed by overt, affixal inflectional morphology across languages. This schema is used to universalize data extracted from Wiktionary via a robust multidimensional table parsing algorithm and feature mapping algorithms, yielding 883,965 instantiated paradigms in 352 languages. These data are shown to be effective for training morphological analyzers, yielding significant accuracy gains when applied to Durrett and DeNero’s (2013) paradigm learning framework.
A Language-Independent Feature Schema for Inflectional Morphology
John Sylak-Glassman,Christo Kirov,David Yarowsky,R. Que
Published 2015 in Annual Meeting of the Association for Computational Linguistics
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- Publication year
2015
- Venue
Annual Meeting of the Association for Computational Linguistics
- Publication date
2015-07-01
- Fields of study
Linguistics, Computer Science
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Semantic Scholar
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