The problem of ambiguity in table question answering

Grijalba, Jorge Osés, Ureña, L. Alfonso, Martínez-Cámara, Eugenio and Camacho Collados, Jose ORCID: https://orcid.org/0000-0003-1618-7239 2026. The problem of ambiguity in table question answering. Presented at: EACL 2026, Rabat, Morocco, 24-29 March 2026. Published in: Demberg, Vera, Inui, Kentaro and Marquez, Lluis eds. Findings of the Association for Computational Linguistics: EACL 2026. Association for Computational Linguistics, pp. 3835-3848. 10.18653/v1/2026.findings-eacl.199

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Abstract

Question Answering on Tabular Data (or Table Question Answering) has seen tremendous advances with the coming of new generation Large Language Models (LLMs). Despite this, significant challenges still remain to be solved if we are to develop robust enough approaches for general usage. One of these is ambiguity in question answering, which historically has not merited much attention due to the previously limited capabilities of LLMs. In this work, we outlay the main types of ambiguousness inherent to tabular data. Then, we discuss how they are influenced by the way our models interact with the information stored in the tables, and we test the capabilities of some LLMs in detecting them. This work provides an initial ground for a deeper discussion on how to approach ambiguity in Tabular Data in the age of LLMs.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Association for Computational Linguistics
ISBN:	9798891763869
Last Modified:	01 Jun 2026 13:45
URI:	https://orca.cardiff.ac.uk/id/eprint/187347

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