@inproceedings{gerald-etal-2024-introducing-cquae,
title = "Introducing {CQ}u{AE} : A New {F}rench Contextualised Question-Answering Corpus for the Education Domain",
author = "Gerald, Thomas and
Vilnat, Anne and
Ettayeb, Sofiane and
Tamames, Louis and
Paroubek, Patrick",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.808",
pages = "9234--9244",
abstract = "We present a new question answering corpus in French designed to educational domain. To be useful in such domain, we have to propose more complex questions and to be able to justify the answers on validated material. We analyze some properties of this corpus. The last part of this paper will be devoted to present the first experiments we have carried out to demonstrate the value of this dataset for learning a Retrieval Augmented Genration framework. Different experiments are proposed, with an automatic evaluation. A human evaluation is proposed to confirm or infirm this automatic evaluation.",
}
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%0 Conference Proceedings
%T Introducing CQuAE : A New French Contextualised Question-Answering Corpus for the Education Domain
%A Gerald, Thomas
%A Vilnat, Anne
%A Ettayeb, Sofiane
%A Tamames, Louis
%A Paroubek, Patrick
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F gerald-etal-2024-introducing-cquae
%X We present a new question answering corpus in French designed to educational domain. To be useful in such domain, we have to propose more complex questions and to be able to justify the answers on validated material. We analyze some properties of this corpus. The last part of this paper will be devoted to present the first experiments we have carried out to demonstrate the value of this dataset for learning a Retrieval Augmented Genration framework. Different experiments are proposed, with an automatic evaluation. A human evaluation is proposed to confirm or infirm this automatic evaluation.
%U https://aclanthology.org/2024.lrec-main.808
%P 9234-9244
Markdown (Informal)
[Introducing CQuAE : A New French Contextualised Question-Answering Corpus for the Education Domain](https://aclanthology.org/2024.lrec-main.808) (Gerald et al., LREC-COLING 2024)
ACL