Generating Irish Text with a Flexible Plug-and-Play Architecture

Simon Mille, Elaine Uí Dhonnchadha, Lauren Cassidy, Brian Davis, Stamatia Dasiopoulou, Anya Belz


Abstract
In this paper, we describe M-FleNS, a multilingual flexible plug-and-play architecture designed to accommodate neural and symbolic modules, and initially instantiated with rule-based modules. We focus on using M-FleNS for the specific purpose of building new resources for Irish, a language currently under-represented in the NLP landscape. We present the general M-FleNS framework and how we use it to build an Irish Natural Language Generation system for verbalising part of the DBpedia ontology and building a multilayered dataset with rich linguistic annotations. Via automatic and human assessments of the output texts we show that with very limited resources we are able to create a system that reaches high levels of fluency and semantic accuracy, while having very low energy and memory requirements.
Anthology ID:
2023.pandl-1.4
Volume:
Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning
Month:
December
Year:
2023
Address:
Singapore
Editors:
Mihai Surdeanu, Ellen Riloff, Laura Chiticariu, Dayne Frietag, Gus Hahn-Powell, Clayton T. Morrison, Enrique Noriega-Atala, Rebecca Sharp, Marco Valenzuela-Escarcega
Venues:
PANDL | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
25–42
Language:
URL:
https://aclanthology.org/2023.pandl-1.4
DOI:
10.18653/v1/2023.pandl-1.4
Bibkey:
Cite (ACL):
Simon Mille, Elaine Uí Dhonnchadha, Lauren Cassidy, Brian Davis, Stamatia Dasiopoulou, and Anya Belz. 2023. Generating Irish Text with a Flexible Plug-and-Play Architecture. In Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning, pages 25–42, Singapore. Association for Computational Linguistics.
Cite (Informal):
Generating Irish Text with a Flexible Plug-and-Play Architecture (Mille et al., PANDL-WS 2023)
Copy Citation:
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 https://preview.aclanthology.org/emnlp-22-attachments/2023.pandl-1.4.mp4