A Pipeline for Extracting Abstract Dependency Templates for Data-to-Text Natural Language Generation

Simon Mille, Josep Ricci, Alexander Shvets, Anya Belz


Abstract
We present work in progress that aims to address the coverage issue faced by rule-based text generators. We propose a pipeline for extracting abstract dependency template (predicate-argument structures) from Wikipedia text to be used as input for generating text from structured data with the FORGe system. The pipeline comprises three main components: (i) candidate sentence retrieval, (ii) clause extraction, ranking and selection, and (iii) conversion to predicate-argument form. We present an approach and preliminary evaluation for the ranking and selection module.
Anthology ID:
2023.depling-1.9
Volume:
Proceedings of the Seventh International Conference on Dependency Linguistics (Depling, GURT/SyntaxFest 2023)
Month:
March
Year:
2023
Address:
Washington, D.C.
Editors:
Owen Rambow, François Lareau
Venues:
DepLing | SyntaxFest
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
91–101
Language:
URL:
https://aclanthology.org/2023.depling-1.9
DOI:
Bibkey:
Cite (ACL):
Simon Mille, Josep Ricci, Alexander Shvets, and Anya Belz. 2023. A Pipeline for Extracting Abstract Dependency Templates for Data-to-Text Natural Language Generation. In Proceedings of the Seventh International Conference on Dependency Linguistics (Depling, GURT/SyntaxFest 2023), pages 91–101, Washington, D.C.. Association for Computational Linguistics.
Cite (Informal):
A Pipeline for Extracting Abstract Dependency Templates for Data-to-Text Natural Language Generation (Mille et al., DepLing-SyntaxFest 2023)
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PDF:
https://preview.aclanthology.org/naacl-24-ws-corrections/2023.depling-1.9.pdf