AITQARetrieval

# AIT-QA 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`. ## Changelog * **[2026-05-10]** Updated `queries.jsonl` with corrected annotations. * *Details:* Fixed [incorrect query annotations and symbolic errors]. * *Version:* Full diff available at [`ea30775`](https://huggingface.co/datasets/ibm-research/AITQARetrieval/commit/ea30775610fb46e17e2bcf85cb570509d528b16d) ## Configs | Config | Description | Split(s) | |---|---|---| | `default` | Relevance judgments (qrels): `qid`, `did`, `score` | `test` | | `queries` | Query IDs, text, answers, type, row hierarchy flag, and paraphrase group | `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: ```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 @misc{katsis2021aitqa, title={AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry}, author={Yannis Katsis and Saneem Chemmengath and Vishwajeet Kumar and Samarth Bharadwaj and Mustafa Canim and Michael Glass and Alfio Gliozzo and Feifei Pan and Jaydeep Sen and Karthik Sankaranarayanan and Soumen Chakrabarti}, year={2021}, eprint={2106.12944}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```