Latin Treebanks in Review: An Evaluation of Morphological Tagging Across Time

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ADA7KHNJ6" target="_blank" >RIV/00216208:11320/25:DA7KHNJ6 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204809265&partnerID=40&md5=c1292301b87f9a90321c2b969df83e5f" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204809265&partnerID=40&md5=c1292301b87f9a90321c2b969df83e5f</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Latin Treebanks in Review: An Evaluation of Morphological Tagging Across Time

Popis výsledku v původním jazyce

Existing Latin treebanks draw from Latin’s long written tradition, spanning 17 centuries and a variety of cultures. Recent efforts have begun to harmonize these treebanks’ annotations to better train and evaluate morphological taggers. However, the heterogeneity of these treebanks must be carefully considered to build effective and reliable data. In this work, we review existing Latin treebanks to identify the texts they draw from, identify their overlap, and document their coverage across time and genre. We additionally design automated conversions of their morphological feature annotations into the conventions of standard Latin grammar. From this, we build new time-period data splits that draw from the existing treebanks which we use to perform a broad cross-time analysis for POS and morphological feature tagging. We find that BERT-based taggers outperform existing taggers while also being more robust to cross-domain shifts. © 2024 Association for Computational Linguistics.

Název v anglickém jazyce

Latin Treebanks in Review: An Evaluation of Morphological Tagging Across Time

Popis výsledku anglicky

Existing Latin treebanks draw from Latin’s long written tradition, spanning 17 centuries and a variety of cultures. Recent efforts have begun to harmonize these treebanks’ annotations to better train and evaluate morphological taggers. However, the heterogeneity of these treebanks must be carefully considered to build effective and reliable data. In this work, we review existing Latin treebanks to identify the texts they draw from, identify their overlap, and document their coverage across time and genre. We additionally design automated conversions of their morphological feature annotations into the conventions of standard Latin grammar. From this, we build new time-period data splits that draw from the existing treebanks which we use to perform a broad cross-time analysis for POS and morphological feature tagging. We find that BERT-based taggers outperform existing taggers while also being more robust to cross-domain shifts. © 2024 Association for Computational Linguistics.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

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

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

ML4AL - Workshop Mach. Learn. Anc. Lang., Proc. Workshop

ISBN

979-889176144-5

ISSN

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e-ISSN

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Počet stran výsledku

16

Strana od-do

203-218

Název nakladatele

Association for Computational Linguistics (ACL)

Místo vydání

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Místo konání akce

Hybrid, Bangkok

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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