mlsanityData to 14 Oct 2026

KGConv, a Conversational Corpus grounded in Wikidata

arXiv 2308.15298 ↗First posted 29 Aug 2023cs.CL cs.AIcited by 1

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Abstract (arXiv)

We present KGConv, a large, conversational corpus of 71k 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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 17 of its 31 references that are in the map. First posted on arXiv 29 Aug 2023.

Builds on

17 of 31 references.

References · 17

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  2. 2018CoQA: A Conversational Question Answering Challengecited by 683
  3. 2018Wizard of Wikipedia: Knowledge-Powered Conversational agentscited by 530
  4. 2017Zero-Shot Relation Extraction via Reading Comprehensioncited by 426
  5. 2018QuAC : Question Answering in Contextcited by 381
  6. 2018Open Domain Question Answering Using Early Fusion of Knowledge Bases and Textcited by 168
  7. 2015Large-scale Simple Question Answering with Memory Networkscited by 127
  8. 2020Text-to-Text Pre-Training for Data-to-Text Taskscited by 104
  9. 2018Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graphcited by 67
  10. 2019Look before you Hop: Conversational Question Answering over Knowledge Graphs Using Judicious Context Expansioncited by 42
  11. 2016Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpuscited by 33
  12. 2022A Well-Composed Text is Half Done! Composition Sampling for Diverse Conditional Generationcited by 28
5 more
  1. 2018Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Typescited by 17
  2. 2021ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversationcited by 12
  3. 2023Semantic Parsing for Conversational Question Answering over Knowledge Graphscited by 10
  4. 2020Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Basescited by 9
  5. 2022CoQAR: Question Rewriting on CoQAcited by 2

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Citing papers per year: 2023: 1.

1 paper.

  1. 2023How Well Do Large Language Models Truly Ground?cited by 14