<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="atanasov-2024-dependency">
    <titleInfo>
        <title>Dependency Parser for Bulgarian</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Atanas</namePart>
        <namePart type="family">Atanasov</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-09</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)</title>
        </titleInfo>
        <originInfo>
            <publisher>Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences</publisher>
            <place>
                <placeTerm type="text">Sofia, Bulgaria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper delves into the implementation of a Biaffine Attention Model, a sophisticated neural network architecture employed for dependency parsing tasks. Proposed by Dozat and Manning, this model is applied to Bulgarian language processing. The model‘s training and evaluation are conducted using the Bulgarian Universal Dependencies dataset. The paper offers a comprehensive explanation of the model‘s architecture and the data preparation process, aiming to demonstrate that for highly inflected languages, the inclusion of two additional input layers - lemmas and language-specific morphological information - is beneficial. The results of the experiments are subsequently presented and discussed. The paper concludes with a reflection on the model‘s performance and suggestions for potential future work.</abstract>
    <identifier type="citekey">atanasov-2024-dependency</identifier>
    <location>
        <url>https://aclanthology.org/2024.clib-1.9/</url>
    </location>
    <part>
        <date>2024-09</date>
        <extent unit="page">
            <start>98</start>
            <end>105</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Dependency Parser for Bulgarian
%A Atanasov, Atanas
%S Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)
%D 2024
%8 September
%I Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
%C Sofia, Bulgaria
%F atanasov-2024-dependency
%X This paper delves into the implementation of a Biaffine Attention Model, a sophisticated neural network architecture employed for dependency parsing tasks. Proposed by Dozat and Manning, this model is applied to Bulgarian language processing. The model‘s training and evaluation are conducted using the Bulgarian Universal Dependencies dataset. The paper offers a comprehensive explanation of the model‘s architecture and the data preparation process, aiming to demonstrate that for highly inflected languages, the inclusion of two additional input layers - lemmas and language-specific morphological information - is beneficial. The results of the experiments are subsequently presented and discussed. The paper concludes with a reflection on the model‘s performance and suggestions for potential future work.
%U https://aclanthology.org/2024.clib-1.9/
%P 98-105

Markdown (Informal)

[Dependency Parser for Bulgarian](https://aclanthology.org/2024.clib-1.9/) (Atanasov, CLIB 2024)

• Dependency Parser for Bulgarian (Atanasov, CLIB 2024)

ACL

• Atanas Atanasov. 2024. Dependency Parser for Bulgarian. In Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024), pages 98–105, Sofia, Bulgaria. Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences.