KGConv, a Conversational Corpus Grounded in Wikidata
Quentin Brabant, Lina M. Rojas Barahona, Gwénolé Lecorvé, Claire Gardent
Abstract
We present KGConv, a large corpus of 71k English conversations where each question-answer pair is grounded in a Wikidata fact. Conversations contain on average 8.6 questions and for each Wikidata fact, we provide multiple variants (12 on average) of the corresponding question using templates, human annotations, hand-crafted rules and a question rewriting neural model. We provide baselines for the task of Knowledge-Based, Conversational Question Generation. KGConv can further be used for other generation and analysis tasks such as single-turn question generation from Wikidata triples, question rewriting, question answering from conversation or from knowledge graphs and quiz generation.- Anthology ID:
- 2024.lrec-main.850
- 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:
- 9732–9742
- Language:
- URL:
- https://aclanthology.org/2024.lrec-main.850
- DOI:
- Cite (ACL):
- Quentin Brabant, Lina M. Rojas Barahona, Gwénolé Lecorvé, and Claire Gardent. 2024. KGConv, a Conversational Corpus Grounded in Wikidata. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 9732–9742, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- KGConv, a Conversational Corpus Grounded in Wikidata (Brabant et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.850.pdf