Do we need to answer that question? Salience and Answerability of Potential Questions in Naturalistic Dialogue
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Computer Science > Computation and Language
Title:Do we need to answer that question? Salience and Answerability of Potential Questions in Naturalistic Dialogue
Abstract:We empirically investigate Question Under Discussion based modelling in naturalistic dialogue by studying whether the salience of generated potential questions predicts their subsequent resolution. Building on Wu et al. (2024), we construct a dataset of 7,124 questions automatically generated from utterances and preceding context from the British National Corpus, and annotated for salience and answerability. We find a robust but low positive correlation between salience and answerability in dialogue, indicating that more salient questions are more likely to be addressed. However, this effect is markedly weaker than in monologic text, suggesting that conversational structure is less predictable. We further observe that structured interactions exhibit stronger alignment between annotators than less organised dialogues.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2609.31130 [cs.CL] |
| (or arXiv:2609.31130v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.31130
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | SEMDIAL 2026 - 30th Workshop on the Semantics and Pragmatics of Dialogue, Sep 2026, Loughborough, United Kingdom |
Submission history
From: Amandine Decker [view email] [via CCSD proxy][v1] Fri, 25 Sep 2026 11:23:45 UTC (1,284 KB)
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