@inproceedings{burchell-etal-2020-querent,
title = "Querent Intent in Multi-Sentence Questions",
author = "Burchell, Laurie and
Chi, Jie and
Hosking, Tom and
Markl, Nina and
Webber, Bonnie",
editor = "Dipper, Stefanie and
Zeldes, Amir",
booktitle = "Proceedings of the 14th Linguistic Annotation Workshop",
month = dec,
year = "2020",
address = "Barcelona, Spain",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.law-1.13",
pages = "138--147",
abstract = "Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit. Following Rhetorical Structure Theory (RST), we recognise that different {``}question discourse relations{''} between the subparts of MSQs reflect different speaker intents, and consequently elicit different answering strategies. Correctly identifying these relations is therefore a crucial step in automatically answering MSQs. We identify five different types of MSQs in English, and define five novel relations to describe them. We extract over 162,000 MSQs from Stack Exchange to enable future research. Finally, we implement a high-precision baseline classifier based on surface features.",
}
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<abstract>Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit. Following Rhetorical Structure Theory (RST), we recognise that different “question discourse relations” between the subparts of MSQs reflect different speaker intents, and consequently elicit different answering strategies. Correctly identifying these relations is therefore a crucial step in automatically answering MSQs. We identify five different types of MSQs in English, and define five novel relations to describe them. We extract over 162,000 MSQs from Stack Exchange to enable future research. Finally, we implement a high-precision baseline classifier based on surface features.</abstract>
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%0 Conference Proceedings
%T Querent Intent in Multi-Sentence Questions
%A Burchell, Laurie
%A Chi, Jie
%A Hosking, Tom
%A Markl, Nina
%A Webber, Bonnie
%Y Dipper, Stefanie
%Y Zeldes, Amir
%S Proceedings of the 14th Linguistic Annotation Workshop
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain
%F burchell-etal-2020-querent
%X Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit. Following Rhetorical Structure Theory (RST), we recognise that different “question discourse relations” between the subparts of MSQs reflect different speaker intents, and consequently elicit different answering strategies. Correctly identifying these relations is therefore a crucial step in automatically answering MSQs. We identify five different types of MSQs in English, and define five novel relations to describe them. We extract over 162,000 MSQs from Stack Exchange to enable future research. Finally, we implement a high-precision baseline classifier based on surface features.
%U https://aclanthology.org/2020.law-1.13
%P 138-147
Markdown (Informal)
[Querent Intent in Multi-Sentence Questions](https://aclanthology.org/2020.law-1.13) (Burchell et al., LAW 2020)
ACL
- Laurie Burchell, Jie Chi, Tom Hosking, Nina Markl, and Bonnie Webber. 2020. Querent Intent in Multi-Sentence Questions. In Proceedings of the 14th Linguistic Annotation Workshop, pages 138–147, Barcelona, Spain. Association for Computational Linguistics.