All datasets / lucacontalbo

lucacontalbo/GRI-QA

314 downloads in 30 days2 likesLast modified 24 Oct 2025View on Hugging Face

Permissive or share-alike

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 705209d
Licence files: No licence file at the top level of the repositoryEvidence: file list at 705209d
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

table-question-answering

Citation text from the card

@inproceedings{contalbo-etal-2025-gri,
    title = "{GRI}-{QA}: a Comprehensive Benchmark for Table Question Answering over Environmental Data",
    author = "Contalbo, Michele Luca  and
      Pederzoli, Sara  and
      Buono, Francesco Del  and
      Valeria, Venturelli  and
      Guerra, Francesco  and
      Paganelli, Matteo",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.findings-acl.814/",
    pages = "15764--15779",
    ISBN = "979-8-89176-256-5",
    abstract = "Assessing corporate environmental sustainability with Table Question Answering systems is challenging due to complex tables, specialized terminology, and the variety of questions they must handle. In this paper, we introduce GRI-QA, a test benchmark designed to evaluate Table QA approaches in the environmental domain. Using GRI standards, we extract and annotate tables from non-financial corporate reports, generating question-answer pairs through a hybrid LLM-human approach. The benchmark includes eight datasets, categorized by the types of operations required, including operations on multiple tables from multiple documents. Our evaluation reveals a significant gap between human and

All datasets marked Permissive or share-alike | JSON

The same facts for your agent

A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.

dataset_licence({ "id": "lucacontalbo/GRI-QA" })
signal: "permissive"
stated_licence: "mit"
sources: 0