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    <titleInfo>
        <title>Kāraka-Based Answer Retrieval for Question Answering in Indic Languages</title>
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    <name type="personal">
        <namePart type="given">Devika</namePart>
        <namePart type="family">Verma</namePart>
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        <namePart type="given">Ramprasad</namePart>
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        <namePart type="family">Joshi</namePart>
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        <namePart type="given">Aiman</namePart>
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        <namePart type="family">Shivani</namePart>
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    <name type="personal">
        <namePart type="given">Rohan</namePart>
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            <namePart type="family">Mitkov</namePart>
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    <abstract>Kārakas from ancient Paninian grammar form a concise set of semantic roles that capture crucial aspect of sentence meaning pivoted on the action verb. In this paper, we propose employing a kāraka-based approach for retrieving answers in Indic question-answering systems. To study and evaluate this novel approach, empirical experiments are conducted over large benchmark corpora in Hindi and Marathi. The results obtained demonstrate the effectiveness of the proposed method. Additionally, we explore the varying impact of two approaches for extracting kārakas. The literature surveyed and experiments conducted encourage hope that kāraka annotation can improve communication with machines using natural languages, particularly in low-resource languages.</abstract>
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        <url>https://aclanthology.org/2023.ranlp-1.129</url>
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        <date>2023-09</date>
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%0 Conference Proceedings
%T Kāraka-Based Answer Retrieval for Question Answering in Indic Languages
%A Verma, Devika
%A Joshi, Ramprasad S.
%A Shivani, Aiman A.
%A Gupta, Rohan D.
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F verma-etal-2023-karaka
%X Kārakas from ancient Paninian grammar form a concise set of semantic roles that capture crucial aspect of sentence meaning pivoted on the action verb. In this paper, we propose employing a kāraka-based approach for retrieving answers in Indic question-answering systems. To study and evaluate this novel approach, empirical experiments are conducted over large benchmark corpora in Hindi and Marathi. The results obtained demonstrate the effectiveness of the proposed method. Additionally, we explore the varying impact of two approaches for extracting kārakas. The literature surveyed and experiments conducted encourage hope that kāraka annotation can improve communication with machines using natural languages, particularly in low-resource languages.
%U https://aclanthology.org/2023.ranlp-1.129
%P 1216-1224

Markdown (Informal)

[Kāraka-Based Answer Retrieval for Question Answering in Indic Languages](https://aclanthology.org/2023.ranlp-1.129) (Verma et al., RANLP 2023)

• Kāraka-Based Answer Retrieval for Question Answering in Indic Languages (Verma et al., RANLP 2023)

ACL

• Devika Verma, Ramprasad S. Joshi, Aiman A. Shivani, and Rohan D. Gupta. 2023. Kāraka-Based Answer Retrieval for Question Answering in Indic Languages. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 1216–1224, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.