Cassidy, Lauren, Lynn, Teresa, Barry, James and Foster, Jennifer ORCID: 0000-0002-7789-4853 (2022) TwittIrish: a universal dependencies treebank of Tweets in modern Irish. In: 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 22-27 May 2022, Dublin, Ireland.
Abstract
Modern Irish is a minority language lacking sufficient computational resources for the task of accurate automatic syntactic parsing of user-generated content such as tweets. Although language technology for the Irish language has been developing in recent years, these tools tend to perform poorly on user-generated content. As with other languages, the linguistic style observed in Irish tweets differs, in terms of orthography, lexicon, and syntax, from that of standard texts more commonly used for the development of language models and parsers. We release the first Universal Dependencies treebank of Irish tweets, facilitating natural language processing of user-generated content in Irish. In this paper, we explore the differences between Irish tweets and standard Irish text, and the challenges associated with dependency parsing of Irish tweets. We describe our bootstrapping method of treebank development and report on preliminary parsing experiments.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Subjects: | Computer Science > Artificial intelligence Computer Science > Computational linguistics Computer Science > Machine learning Humanities > Irish language Humanities > Language |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Published in: | Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics. 1. Association for Computational Linguistics (ACL). |
Publisher: | Association for Computational Linguistics (ACL) |
Official URL: | https://doi.org/10.18653/v1/2022.acl-long.473 |
Copyright Information: | © 2022 Association for Computational Linguistics |
Funders: | Irish Government Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media under the GaelTech Projec, Science Foundation Ireland in the ADAPT Centre (Grant No. 13/RC/2106) at Dublin City University. |
ID Code: | 29142 |
Deposited On: | 19 Oct 2023 11:29 by Jennifer Foster . Last Modified 19 Oct 2023 13:23 |
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