Datasets › SPARTQA
SPARTQA (SPAtial Reasoning on Textual Question Answering)
SpartQA is a textual question answering benchmark for spatial reasoning on natural language text which contains more realistic spatial phenomena not covered by prior datasets and that is challenging for state-of-the-art language models (LM).
SPARTQA is built on NLVR’s images containing more objects with richer spatial structures. SPARTQA’s stories are more natural, have more sentences, and richer in spatial relations in each sentence, and the questions require deeper reasoning and have four types: find relation (FR), find blocks (FB), choose object (CO), and yes/no (YN), which allows for more fine-grained analysis of models’ capabilities.
https://aclanthology.org/2021.naacl-main.364/
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 9 papers for it but never published that list.
Dataset loaders archive 2025-07-28
1 loader as listed in the archive; links are outbound and not re-checked here.
Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
Variants archive 2025-07-28
- SPARTQA
1 variant name, as the archive lists them.
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