Modeling the Quality of Dialogical Explanations

Milad Alshomary, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp Cimiano, Henning Wachsmuth


Abstract
Explanations are pervasive in our lives. Mostly, they occur in dialogical form where an explainer discusses a concept or phenomenon of interest with an explainee. Leaving the explainee with a clear understanding is not straightforward due to the knowledge gap between the two participants. Previous research looked at the interaction of explanation moves, dialogue acts, and topics in successful dialogues with expert explainers. However, daily-life explanations often fail, raising the question of what makes a dialogue successful. In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee’s side. In particular, we first construct a corpus of 399 dialogues from the Reddit forum Explain Like I am Five and annotate it for interaction flows and explanation quality. We then analyze the interaction flows, comparing them to those appearing in expert dialogues. Finally, we encode the interaction flows using two language models that can handle long inputs, and we provide empirical evidence for the effectiveness boost gained through the encoding in predicting the success of explanation dialogues.
Anthology ID:
2024.lrec-main.1007
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
11523–11536
Language:
URL:
https://aclanthology.org/2024.lrec-main.1007
DOI:
Bibkey:
Cite (ACL):
Milad Alshomary, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp Cimiano, and Henning Wachsmuth. 2024. Modeling the Quality of Dialogical Explanations. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11523–11536, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Modeling the Quality of Dialogical Explanations (Alshomary et al., LREC-COLING 2024)
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PDF:
https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.1007.pdf