UDParse @ SIGTYP 2024 Shared Task: Modern Language Models for Historical Languages
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AADUHP93P" target="_blank" >RIV/00216208:11320/25:ADUHP93P - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189630518&partnerID=40&md5=d11e00a79b191c385d6d7e08f310566d" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189630518&partnerID=40&md5=d11e00a79b191c385d6d7e08f310566d</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
UDParse @ SIGTYP 2024 Shared Task: Modern Language Models for Historical Languages
Original language description
SIGTYP’s Shared Task on Word Embedding Evaluation for Ancient and Historical Languages was proposed in two variants, constrained or unconstrained. Whereas the constrained variant disallowed any other data to train embeddings or models than the data provided, the unconstrained variant did not have these limits. We participated in the five tasks of the unconstrained variant and came out first. The tasks were the prediction of part-of-speech, lemmas and morphological features and filling masked words and masked characters on 16 historical languages. We decided to use a dependency parser and train the data using an underlying pretrained transformer model to predict part-of-speech tags, lemmas, and morphological features. For predicting masked words, we used multilingual distilBERT (with rather bad results). In order to predict masked characters, our language model is extremely small: it is a model of 5-gram frequencies, obtained by reading the available training data. © 2024 Association for Computational Linguistics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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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
SIGTYP - Workshop Res. Comput. Linguist. Typology Multiling. NLP, Proc. Workshop
ISBN
979-889176071-4
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
142-150
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
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Event location
St. Julian's, Malta
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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