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Nostra Domina at EvaLatin 2024: Improving Latin Polarity Detection through Data Augmentation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AGQ8FT4KA" target="_blank" >RIV/00216208:11320/25:GQ8FT4KA - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195205724&partnerID=40&md5=bc16136cb13a2241bf1ac80d5041051b" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195205724&partnerID=40&md5=bc16136cb13a2241bf1ac80d5041051b</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Nostra Domina at EvaLatin 2024: Improving Latin Polarity Detection through Data Augmentation

  • Original language description

    This paper describes submissions from the team Nostra Domina to the EvaLatin 2024 shared task of emotion polarity detection. Given the low-resource environment of Latin and the complexity of sentiment in rhetorical genres like poetry, we augmented the available data through automatic polarity annotation. We present two methods for doing so on the basis of the k-means algorithm, and we employ a variety of Latin large language models (LLMs) in a neural architecture to better capture the underlying contextual sentiment representations. Our best approach achieved the second highest macro-averaged Macro-F1 score on the shared task’s test set. © 2024 ELRA Language Resources Association: CC BY-NC 4.0.

  • 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

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Workshop Lang. Technol. Hist. Anc. Lang., LT4HALA LREC-COLING - Workshop Proc.

  • ISBN

    978-249381446-3

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    215-222

  • Publisher name

    European Language Resources Association (ELRA)

  • Place of publication

  • Event location

    Torino, Italia

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article