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Towards electronic lexicography for the Kurdish language

Authors: Ahmadi, Sina; Hassani, Hossein; McCrae, John P.;

Towards electronic lexicography for the Kurdish language

Abstract

This paper describes the development of lexicographic resources for Kurdish and provides a lexical model for this language. Kurdish is considered a less-resourced language, and currently, lacks machine-readable lexical resources. The unique potential which Linked Data and the Semantic Web offer to e-lexicography enables interoperability across lexical resources by elevating the traditional linguistic data to machine-processable semantic formats. Therefore, we present our lexicon in Ontolex-Lemon ontology as a standard model for sharing lexical information on the Semantic Web. The research covers the Sorani, Kurmanji, and Hawrami dialects of Kurdish. This research suggests that although Kurdish is a less-resourced language, in terms of documented lexicons, it has a wide range of resources, but because they are not machine-readable they could not contribute to the language processing. The outcome of this project, which is made publicly available, assists scholars in their efforts towards making Kurdish a resource-rich language.

Country
Ireland
Keywords

less-resourced languages, e-lexicography, Kurdish, machine-readable dictionary, Data Science Institute

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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