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        <title>Know Your Graph. State-of-the-Art Knowledge-Based WSD</title>
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    <name type="personal">
        <namePart type="given">Alexander</namePart>
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        <namePart type="given">Kiril</namePart>
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    <name type="personal">
        <namePart type="given">Petya</namePart>
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            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)</title>
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    <abstract>This paper introduces several improvements over the current state of the art in knowledge-based word sense disambiguation. Those innovations are the result of modifying and enriching a knowledge base created originally on the basis of WordNet. They reflect several separate but connected strategies: manipulating the shape and the content of the knowledge base, assigning weights over the relations in the knowledge base, and the addition of new relations to it. The main contribution of the paper is to demonstrate that the previously proposed knowledge bases organize linguistic and world knowledge suboptimally for the task of word sense disambiguation. In doing so, the paper also establishes a new state of the art for knowledge-based approaches. Its best models are competitive in the broader context of supervised systems as well.</abstract>
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    <identifier type="doi">10.26615/978-954-452-056-4_110</identifier>
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        <url>https://aclanthology.org/R19-1110</url>
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        <date>2019-sep</date>
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%0 Conference Proceedings
%T Know Your Graph. State-of-the-Art Knowledge-Based WSD
%A Popov, Alexander
%A Simov, Kiril
%A Osenova, Petya
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 sep
%I INCOMA Ltd.
%C Varna, Bulgaria
%F popov-etal-2019-know
%X This paper introduces several improvements over the current state of the art in knowledge-based word sense disambiguation. Those innovations are the result of modifying and enriching a knowledge base created originally on the basis of WordNet. They reflect several separate but connected strategies: manipulating the shape and the content of the knowledge base, assigning weights over the relations in the knowledge base, and the addition of new relations to it. The main contribution of the paper is to demonstrate that the previously proposed knowledge bases organize linguistic and world knowledge suboptimally for the task of word sense disambiguation. In doing so, the paper also establishes a new state of the art for knowledge-based approaches. Its best models are competitive in the broader context of supervised systems as well.
%R 10.26615/978-954-452-056-4_110
%U https://aclanthology.org/R19-1110
%U https://doi.org/10.26615/978-954-452-056-4_110
%P 949-958

Markdown (Informal)

[Know Your Graph. State-of-the-Art Knowledge-Based WSD](https://aclanthology.org/R19-1110) (Popov et al., RANLP 2019)

• Know Your Graph. State-of-the-Art Knowledge-Based WSD (Popov et al., RANLP 2019)

ACL

• Alexander Popov, Kiril Simov, and Petya Osenova. 2019. Know Your Graph. State-of-the-Art Knowledge-Based WSD. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 949–958, Varna, Bulgaria. INCOMA Ltd..