Papers with KGConv

1 papers
KGConv, a Conversational Corpus Grounded in Wikidata (2024.lrec-main)

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Challenge: a large corpus of 71k English conversations contains on average 8.6 questions . Unlike open domain and task-oriented dialogues, information seeking conversations are driven by the desire to acquire or evaluate knowledge.
Approach: They propose a large corpus of 71k English conversations where each question-answer pair is grounded in a Wikidata fact.
Outcome: The proposed dataset can be used for knowledge-based, conversational question generation . it can also be used to generate single-turn questions from Wikidata triples, question rewriting, question answering from conversation or knowledge graphs and quiz generation.

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