Do we need to answer that question? Salience and Answerability of Potential Questions in Naturalistic Dialogue

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.

Computation and Language (cs.CL)

arXiv:2609.31130 [cs.CL]

(or arXiv:2609.31130v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.31130 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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