Yamini Chandrashekar


2022

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Language Diversity: Visible to Humans, Exploitable by Machines
Gábor Bella | Erdenebileg Byambadorj | Yamini Chandrashekar | Khuyagbaatar Batsuren | Danish Cheema | Fausto Giunchiglia
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

The Universal Knowledge Core (UKC) is a large multilingual lexical database with a focus on language diversity and covering over two thousand languages. The aim of the database, as well as its tools and data catalogue, is to make the abstract notion of linguistic diversity visually understandable for humans and formally exploitable by machines. The UKC website lets users explore millions of individual words and their meanings, but also phenomena of cross-lingual convergence and divergence, such as shared interlingual meanings, lexicon similarities, cognate clusters, or lexical gaps. The UKC LiveLanguage Catalogue, in turn, provides access to the underlying lexical data in a computer-processable form, ready to be reused in cross-lingual applications.

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Using Linguistic Typology to Enrich Multilingual Lexicons: the Case of Lexical Gaps in Kinship
Temuulen Khishigsuren | Gábor Bella | Khuyagbaatar Batsuren | Abed Alhakim Freihat | Nandu Chandran Nair | Amarsanaa Ganbold | Hadi Khalilia | Yamini Chandrashekar | Fausto Giunchiglia
Proceedings of the Thirteenth Language Resources and Evaluation Conference

This paper describes a method to enrich lexical resources with content relating to linguistic diversity, based on knowledge from the field of lexical typology. We capture the phenomenon of diversity through the notion of lexical gap and use a systematic method to infer gaps semi-automatically on a large scale, which we demonstrate on the kinship domain. The resulting free diversity-aware terminological resource consists of 198 concepts, 1,911 words, and 37,370 gaps in 699 languages. We see great potential in the use of resources such as ours for the improvement of a variety of cross-lingual NLP tasks, which we illustrate through an application in the evaluation of machine translation systems.

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IndoUKC: A Concept-Centered Indian Multilingual Lexical Resource
Nandu Chandran Nair | Rajendran S. Velayuthan | Yamini Chandrashekar | Gábor Bella | Fausto Giunchiglia
Proceedings of the Thirteenth Language Resources and Evaluation Conference

We introduce the IndoUKC, a new multilingual lexical database comprised of eighteen Indian languages, with a focus on formally capturing words and word meanings specific to Indian languages and cultures. The IndoUKC reuses content from the existing IndoWordNet resource while providing a new model for the cross-lingual mapping of lexical meanings that allows for a richer, diversity-aware representation. Accordingly, beyond a thorough syntactic and semantic cleaning, the IndoWordNet lexical content has been thoroughly remodeled in order to allow a more precise expression of language-specific meaning. The resulting database is made available both for browsing through a graphical web interface and for download through the LiveLanguage data catalogue.

2020

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A Major Wordnet for a Minority Language: Scottish Gaelic
Gábor Bella | Fiona McNeill | Rody Gorman | Caoimhin O Donnaile | Kirsty MacDonald | Yamini Chandrashekar | Abed Alhakim Freihat | Fausto Giunchiglia
Proceedings of the Twelfth Language Resources and Evaluation Conference

We present a new wordnet resource for Scottish Gaelic, a Celtic minority language spoken by about 60,000 speakers, most of whom live in Northwestern Scotland. The wordnet contains over 15 thousand word senses and was constructed by merging ten thousand new, high-quality translations, provided and validated by language experts, with an existing wordnet derived from Wiktionary. This new, considerably extended wordnet—currently among the 30 largest in the world—targets multiple communities: language speakers and learners; linguists; computer scientists solving problems related to natural language processing. By publishing it as a freely downloadable resource, we hope to contribute to the long-term preservation of Scottish Gaelic as a living language, both offline and on the Web.