HotpotQA Dataset

A HotpotQA Dataset is a QA dataset that is a large-scale dataset for developing QA systems that can perform explainable, multi-hop reasoning over multiple natural languages.

• AKA: HotpotQA Corpus, HotpotQA.
• Context:
  • Website: https://hotpotqa.github.io
  • First developed by Yang et al. (2018).
  • …
• Example(s):
  • HotpotQA Training Dataset,
  • HotpotQA Dev (Distractor) Dataset,
  • HotpotQA Dev (fullwiki) Dataset,
  • HotpotQA Test (fullwiki) Dataset,
  • …
• Counter-Example(s):
  • a CoQA Dataset,
  • a MS COCO Dataset,
  • a NarrativeQA Dataset,
  • a Natural Questions Dataset,
  • a NewsQA Dataset,
  • a QuAC Dataset,
  • a RACE Dataset,
  • a SearchQA Dataset,
  • a SQuAD Dataset,
  • a TriviaQA Dataset,
  • a WikiQA Dataset.
• See: Question-Answering System, Natural Language Processing Task, Natural Language Understanding Task, Natural Language Generation Task.

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References

2018

• (Yang et al., 2018) ⇒ Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. (2018). “HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.” In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP 2018).
  • QUOTE: We present HOTPOTQA, a large-scale question answering dataset aimed at facilitating the development of QA systems capable of performing explainable, multi-hop reasoning over diverse natural language.

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