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Kāraka-Based Answer Retrieval for Question Answering in Indic Languages

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AA598BFLU" target="_blank" >RIV/00216208:11320/23:A598BFLU - isvavai.cz</a>

  • Result on the web

    <a href="https://aclanthology.org/2023.ranlp-1.129/" target="_blank" >https://aclanthology.org/2023.ranlp-1.129/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Kāraka-Based Answer Retrieval for Question Answering in Indic Languages

  • Original language description

    "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."

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    "Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing"

  • ISBN

    978-954-452-092-2

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    1216-1224

  • Publisher name

    INCOMA Ltd. Shoumen, BULGARIA

  • Place of publication

    Varna, Bulgaria

  • Event location

    Varna, Bulgaria

  • Event date

    Jan 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article