KGConv, a Conversational Corpus grounded in Wikidata
Résumé
We present KGConv, a large corpus of 71k English conversations where each question-answer pair is grounded in a Wikidata fact. The conversations were generated automatically: in particular, questions were created using a collection of 10,355 templates; subsequently, the naturalness of conversations was improved by inserting ellipses and coreference into questions, via both handcrafted rules and a generative rewriting model. The dataset thus provides several variants of each question (12 on average), organized into 3 levels of conversationality. 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.
Domaines
Informatique [cs]Origine | Fichiers produits par l'(les) auteur(s) |
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