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ibm-research/OTTQASmallRetrieval

OTT-QA Retrieval This dataset is part of a Table + Text retrieval benchmark. Includes queries and relevance judgments across dev split(s), with corpus in 3 format(s): corpus_linearized, corpus_md, corpus_structure. Configs Config Description Split(s) default Relevance judgments (qrels): qid, did, score dev queries Query IDs and text dev_queries corpus_linearized Linearized table representation corpus_linearized corpus_md Markdown table… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/OTTQASmallRetrieval.

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OTT-QA Retrieval

This dataset is part of a Table + Text retrieval benchmark. Includes queries and relevance judgments across dev split(s), with corpus in 3 format(s): corpus_linearized, corpus_md, corpus_structure.

Configs

ConfigDescriptionSplit(s)
defaultRelevance judgments (qrels): qid, did, scoredev
queriesQuery IDs and textdev_queries
corpus_linearizedLinearized table representationcorpus_linearized
corpus_mdMarkdown table representationcorpus_md
corpus_structureStructured corpus with headers, cells, meta_data. text field corresponds to linearized Text + Table.corpus_structure

corpus_structure additional fields

FieldTypeDescription
meta_datastringTable metadata / caption
headerslist[string]Column headers
cellslist[string]Flattened cell values

TableIR Benchmark Statistics

DatasetStructured#Train#Dev#Test#Corpus
OpenWikiTables✓53.8k6.6k6.6k24.7k
NQTables✓9.6k1.1k1k170k
FeTaQA✓7.3k1k2k10.3k
OTT-QA (small)✓41.5k2.2k--8.8k
MultiHierTT✗--929--9.9k
AIT-QA✗----5151.9k
StatcanRetrieval✗----8705.9k
watsonxDocsQA✗----301.1k

Citation

If you use TableIR Eval: Table-Text IR Evaluation Collection, please cite:

bibtex
@misc{doshi2026tableir,
  title        = {TableIR Eval: Table-Text IR Evaluation Collection},
  author       = {Doshi, Meet and Boni, Odellia and Kumar, Vishwajeet and Sen, Jaydeep and Joshi, Sachindra},
  year         = {2026},
  institution  = {IBM Research},
  howpublished = {https://huggingface.co/collections/ibm-research/table-text-ir-evaluation},
  note         = {Hugging Face dataset collection}
}

All credit goes to original authors. Please cite their work:

bibtex
@article{chen2021ottqa,
  title={Open Question Answering over Tables and Text},
  author={Wenhu Chen, Ming-wei Chang, Eva Schlinger, William Wang, William Cohen},
  journal={Proceedings of ICLR 2021},
  year={2021}
}