FeTaQARetrieval

# FeTaQA Retrieval Table retrieval benchmark dataset. Includes queries and relevance judgments across test split(s), with corpus in 2 format(s): `corpus_md`, `corpus_structure`. ## Configs | Config | Description | Split(s) | |---|---|---| | `default` | Relevance judgments (qrels): `qid`, `did`, `score` | `test` | | `queries` | Query IDs and text | `test_queries` | | `corpus_md` | Markdown table representation | `corpus_md` | | `corpus_structure` | Structured corpus with `headers`, `cells`, `meta_data`. `text` field corresponds to linearized Text + Table. | `corpus_structure` | ## `corpus_structure` additional fields | Field | Type | Description | |---|---|---| | `meta_data` | string | Table metadata / caption | | `headers` | list[string] | Column headers | | `cells` | list[string] | Flattened cell values | ## 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: ```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{Nan2021FeTaQAFT, title={FeTaQA: Free-form Table Question Answering}, author={Nan, Linyong and Hsieh, Chiachun and Mao, Ziming and Lin, Xi Victoria and Verma, Neha and Zhang, Rui and Kryściński, Wojciech and Schoelkopf, Hailey and Kong, Riley and Tang, Xiangru and Mutuma, Mutethia and Rosand, Ben and Trindade, Isabel and Bandaru, Renusree and Cunningham, Jacob and Xiong, Caiming and Radev, Dragomir}, journal={Transactions of the Association for Computational Linguistics}, year={2022}, volume={10}, pages={35-49} } ```