Clarifying Underspecified Discourse Relations in Instructional Texts

Berfin Aktas, Michael Roth


Abstract
Discourse relations contribute to the structure of a text and can optionally be realized through explicit connectives such as “but” and “while”. But when are these connectives necessary to avoid possible misunderstandings? We investigate this question by first building a corpus of 4,274 text revisions in each of which a connective was explicitly inserted. For a subset of 250 cases, we collect plausibility annotations on other connectives to check whether they would represent suitable alternative relations. The results of this annotation show that several relations are often perceived as plausible in our data. Furthermore, we analyze the extent to which large language models can identify instances with multiple plausible relations as a possible source of misunderstandings. We find that the models predict plausibility of individual connectives with up to 66% accuracy, but they are not reliable in estimating when multiple relations are plausible.
Anthology ID:
2025.findings-acl.633
Volume:
Findings of the Association for Computational Linguistics: ACL 2025
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Wanxiang Che, Joyce Nabende, Ekaterina Shutova, Mohammad Taher Pilehvar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
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Pages:
12237–12256
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URL:
https://preview.aclanthology.org/display_plenaries/2025.findings-acl.633/
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Bibkey:
Cite (ACL):
Berfin Aktas and Michael Roth. 2025. Clarifying Underspecified Discourse Relations in Instructional Texts. In Findings of the Association for Computational Linguistics: ACL 2025, pages 12237–12256, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Clarifying Underspecified Discourse Relations in Instructional Texts (Aktas & Roth, Findings 2025)
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PDF:
https://preview.aclanthology.org/display_plenaries/2025.findings-acl.633.pdf