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SemEval 2025

Task 8: Question Answering on Tabular Data

  • Task Overview: SemEval 2025 focuses on Question Answering over Tabular Data using the DataBench benchmark.
  • DataBench Description:
    • Composed of real-world table datasets.
    • Features large sizes with numerous rows and columns.
    • Contains a variety of data types to assess different question types.
  • Participant Objectives:
    • Develop systems to answer questions based on day-to-day datasets.
    • Answers can be numerical, categorical, boolean, or lists.
  • Data Usage:
    • DataBench can be used for training and validation.
    • A separate test set will be provided for competition.
  • Task Format:
    • Participants will receive (dataset, question) pairs.
    • Answers will be compared against a gold standard.
  • Methods:
    • Two example approaches: In-Context Learning and Code Generation.
    • Participants can use these or develop their own methods.

Dataset Link