A Crosslingual Approach to Dependency Parsing for Middle High German

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A3JQSCQKF" target="_blank" >RIV/00216208:11320/25:3JQSCQKF - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216754532&partnerID=40&md5=bc144ac916cb517c9128285b894c44f9" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216754532&partnerID=40&md5=bc144ac916cb517c9128285b894c44f9</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A Crosslingual Approach to Dependency Parsing for Middle High German

Popis výsledku v původním jazyce

This work presents the development and evaluation of a dependency parser for Middle High German Universal Dependencies utilising modern German as a support language for low-resource MHG. A neural dependency parser is trained with Stanza achieving UAS = 92.95 and LAS = 88.06. To ensure the parser’s utility in facilitating and speeding up manual annotation to build a scaling UD treebank of MHG, a thorough error analysis shows the model’s structural reliability as well as frequently confused labels. Hence, this work constitutes an effort to counterbalance the under-representation of historical languages in dependency treebanks and attend to the need of historical treebanks in contemporary linguistic research by utilising the UD extensions and accordingly annotated corpora published by Dipper et al. (2024). ©2024 Association for Computational Linguistics.

Název v anglickém jazyce

A Crosslingual Approach to Dependency Parsing for Middle High German

Popis výsledku anglicky

This work presents the development and evaluation of a dependency parser for Middle High German Universal Dependencies utilising modern German as a support language for low-resource MHG. A neural dependency parser is trained with Stanza achieving UAS = 92.95 and LAS = 88.06. To ensure the parser’s utility in facilitating and speeding up manual annotation to build a scaling UD treebank of MHG, a thorough error analysis shows the model’s structural reliability as well as frequently confused labels. Hence, this work constitutes an effort to counterbalance the under-representation of historical languages in dependency treebanks and attend to the need of historical treebanks in contemporary linguistic research by utilising the UD extensions and accordingly annotated corpora published by Dipper et al. (2024). ©2024 Association for Computational Linguistics.

Druh

O - Ostatní výsledky

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