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.