Building UD Cairo for Old English in the Classroom

Lauren Levine, Junghyun Min, Amir Zeldes


Abstract
In this paper we present a sample treebank for Old English based on the UD Cairo sentences, collected and annotated as part of a classroom curriculum in Historical Linguistics. To collect the data, a sample of 20 sentences illustrating a range of syntactic constructions in the world’s languages, we employ a combination of LLM prompting and searches in authentic Old English data. For annotation we assigned sentences to multiple students with limited prior exposure to UD, whose annotations we compare and adjudicate. Our results suggest that while current LLM outputs in Old English do not reflect authentic syntax, this can be mitigated by post-editing, and that although beginner annotators do not possess enough background to complete the task perfectly, taken together they can produce good results and learn from the experience. We also conduct preliminary parsing experiments using Modern English training data, and find that although performance on Old English is poor, parsing on annotated features (lemma, hyperlemma, gloss) leads to improved performance.
Anthology ID:
2025.udw-1.10
Volume:
Proceedings of the Eighth Workshop on Universal Dependencies (UDW, SyntaxFest 2025)
Month:
August
Year:
2025
Address:
Ljubljana, Slovenia
Editors:
Gosse Bomma, Çağrı Çöltekin
Venues:
UDW | WS | SyntaxFest
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
97–104
Language:
URL:
https://preview.aclanthology.org/transition-to-people-yaml/2025.udw-1.10/
DOI:
Bibkey:
Cite (ACL):
Lauren Levine, Junghyun Min, and Amir Zeldes. 2025. Building UD Cairo for Old English in the Classroom. In Proceedings of the Eighth Workshop on Universal Dependencies (UDW, SyntaxFest 2025), pages 97–104, Ljubljana, Slovenia. Association for Computational Linguistics.
Cite (Informal):
Building UD Cairo for Old English in the Classroom (Levine et al., UDW-SyntaxFest 2025)
Copy Citation:
PDF:
https://preview.aclanthology.org/transition-to-people-yaml/2025.udw-1.10.pdf