Abstract
This paper addresses structural ambiguity in Dutch relative clauses. By investigating the task of disambiguation by grounding, we study how the presence of a prior sentence can resolve relative clause ambiguities. We apply this method to two parsing architectures in an attempt to demystify the parsing and language model components of two present-day neural parsers. Results show that a neurosymbolic parser, based on proof nets, is more open to data bias correction than an approach based on universal dependencies, although both set-ups suffer from a comparable initial data bias.- Anthology ID:
- 2023.conll-1.11
- Volume:
- Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Jing Jiang, David Reitter, Shumin Deng
- Venue:
- CoNLL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 155–164
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.conll-1.11/
- DOI:
- 10.18653/v1/2023.conll-1.11
- Cite (ACL):
- Gijs Wijnholds and Michael Moortgat. 2023. Structural Ambiguity and its Disambiguation in Language Model Based Parsers: the Case of Dutch Clause Relativization. In Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL), pages 155–164, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Structural Ambiguity and its Disambiguation in Language Model Based Parsers: the Case of Dutch Clause Relativization (Wijnholds & Moortgat, CoNLL 2023)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2023.conll-1.11.pdf