ibm-research/WatsonxDocsQARetrieval

WatsonxDocsQA Retrieval

This dataset is part of a Table + Text retrieval benchmark. Includes queries and relevance judgments across test split(s), with corpus in 1 format(s): corpus.

Configs

Config	Description	Split(s)
default	Relevance judgments (qrels): qid, did, score	test
queries	Query IDs and text	test_queries
corpus	Plain text corpus: _id, title, text	corpus

TableIR Benchmark Statistics

Dataset	Structured	#Train	#Dev	#Test	#Corpus
OpenWikiTables	✓	53.8k	6.6k	6.6k	24.7k
NQTables	✓	9.6k	1.1k	1k	170k
FeTaQA	✓	7.3k	1k	2k	10.3k
OTT-QA (small)	✓	41.5k	2.2k	--	8.8k
MultiHierTT	✗	--	929	--	9.9k
AIT-QA	✗	--	--	515	1.9k
StatcanRetrieval	✗	--	--	870	5.9k
watsonxDocsQA	✗	--	--	30	1.1k

Citation

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

@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}
}

This repository is just a reformatted version of ibm-research/watsonxDocsQA.

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

@misc{orbach2025analysishyperparameteroptimizationmethods,
      title={An Analysis of Hyper-Parameter Optimization Methods for Retrieval Augmented Generation}, 
      author={Matan Orbach and Ohad Eytan and Benjamin Sznajder and Ariel Gera and Odellia Boni and Yoav Kantor and Gal Bloch and Omri Levy and Hadas Abraham and Nitzan Barzilay and Eyal Shnarch and Michael E. Factor and Shila Ofek-Koifman and Paula Ta-Shma and Assaf Toledo},
      year={2025},
      eprint={2505.03452},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2505.03452}, 
}