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RETECO — Reasoning-Oriented Retrieval

Website · Task · Data & Corpora · Sample Data · Evaluation · Papers · Participate

RETECO is a SemEval-2027 shared task on retrieval that must reason over temporal constraints and multi-turn conversational context. It asks whether retrieval and RAG systems can identify evidence that is relevant because of when it applies and what the conversation has already established.

RETECO has been accepted as a SemEval-2027 shared task.

Read the final task proposal

Tracks

Track Sub-track Required output Official retrieval score
1 · Temporal Grounded Retrieval 1a Temporal Retrieval Ranked documents per query nDCG@10
1 · Temporal Grounded Retrieval 1b Step-wise Retrieval Ranked documents per supplied step Step-level nDCG@10
2 · Conversational Retrieval 2a Conversational Retrieval Ranked passages per target turn nDCG@10
2 · Conversational Retrieval 2b Gold-Passage Generation Grounded answer Five generation dimensions
2 · Conversational Retrieval 2c Full Conversational RAG Ranked passages + grounded answer nDCG@10; generation reported alongside

See the full task definitions and evaluation plan.

Sample data

The repository contains a compact, human-inspected package copied from the official TEMPO and RECOR releases:

  • Track 1: 5 TEMPO examples, 26 supporting passages, and 26 positive qrels.
  • Track 2: 4 RECOR conversations containing 13 turns, 15 supporting passages, and 32 positive qrels.
  • A manifest pins the source dataset revisions and selected record IDs.

Inspect samples online · Download the ZIP · Browse source files

The sample is a format and feasibility demonstration—not a new benchmark split and not the hidden SemEval test set. It contains only referenced positive evidence, so retrieval systems must not be evaluated against the sample corpus alone.

Data and corpora

Track 1: TEMPO

TEMPO contains 1,730 complex temporal queries, 3,976 decomposed retrieval steps, and 1,654,055 documents across 13 independent domain corpora.

Group Domain Queries Corpus documents
Blockchain Bitcoin 100 153,291
Blockchain Cardano 51 87,201
Blockchain IOTA 10 10,372
Blockchain Monero 65 85,093
Social Sciences Economics 83 93,756
Social Sciences Law 35 43,288
Social Sciences Politics 150 183,394
Social Sciences History 801 356,493
Applied Quantitative Finance 34 28,785
Applied Travel 100 177,677
Applied Workplace 36 64,659
Applied Genealogy 115 156,228
STEM History of Science and Mathematics 150 213,818
Total 13 domains 1,730 1,654,055

Track 2: RECOR

RECOR contains 707 conversations, 2,971 target turns, and 507,141 documents across 11 domain corpora. Six domains come from BRIGHT and five from StackExchange.

Source Domain Conversations Turns Corpus documents
BRIGHT Biology 85 362 57,359
BRIGHT Earth Science 98 454 121,249
BRIGHT Economics 74 288 50,220
BRIGHT Psychology 84 333 52,835
BRIGHT Robotics 68 259 61,961
BRIGHT Sustainable Living 78 319 60,792
StackExchange Drones 37 142 16,381
StackExchange Hardware 46 188 26,308
StackExchange Law 50 230 20,027
StackExchange Medical Sciences 44 183 23,297
StackExchange Politics 43 213 16,712
Total 11 domains 707 2,971 507,141

The public benchmarks support training and development. Final SemEval scoring uses a separate, never-publicly-released test set with private gold judgments.

Papers

TEMPO

TEMPO: A Realistic Multi-Domain Benchmark for Temporal Reasoning-Intensive Retrieval
Abdelrahman Abdallah, Mohammed Ali, Muhammad Abdul-Mageed, and Adam Jatowt.
arXiv:2601.09523, 2026. Paper

@article{abdallah2026tempo,
  title={TEMPO: A Realistic Multi-Domain Benchmark for Temporal Reasoning-Intensive Retrieval},
  author={Abdallah, Abdelrahman and Ali, Mohammed and Abdul-Mageed, Muhammad and Jatowt, Adam},
  journal={arXiv preprint arXiv:2601.09523},
  year={2026},
  url={https://arxiv.org/abs/2601.09523}
}

RECOR

RECOR: Reasoning-focused Multi-turn Conversational Retrieval Benchmark
Mohammed Ali, Abdelrahman Abdallah, Amit Agarwal, Hitesh Laxmichand Patel, and Adam Jatowt.
Findings of ACL 2026, pages 2688–2723. Paper · DOI

@inproceedings{ali2026recor,
  title={RECOR: Reasoning-focused Multi-turn Conversational Retrieval Benchmark},
  author={Ali, Mohammed and Abdallah, Abdelrahman and Agarwal, Amit and Patel, Hitesh Laxmichand and Jatowt, Adam},
  booktitle={Findings of the Association for Computational Linguistics: ACL 2026},
  pages={2688--2723},
  year={2026},
  publisher={Association for Computational Linguistics},
  doi={10.18653/v1/2026.findings-acl.129},
  url={https://aclanthology.org/2026.findings-acl.129/}
}

Both records are available in CITATIONS.bib. The official RETECO task-paper citation will be added after the SemEval-2027 task description is published.

Repository map

RETECO/
├── docs/                         # GitHub Pages website
│   ├── index.html
│   ├── task.html
│   ├── data.html                 # Detailed per-domain corpora
│   ├── samples.html              # Human-readable examples
│   ├── evaluation.html
│   ├── papers.html               # Proposal, papers, citations
│   ├── participate.html
│   ├── timeline.html
│   ├── sample_data/              # Curated machine-readable sample
│   └── assets/
│       ├── downloads/
│       └── papers/
├── .github/workflows/            # Pages deployment
├── CITATIONS.bib
├── CONTRIBUTING.md
├── CODE_OF_CONDUCT.md
├── SECURITY.md
└── README.md

Competition format checkers, local scorers, starter baselines, and sample submissions will be added when their SemEval interfaces are frozen.

Local website preview

The website is dependency-free:

python -m http.server 8000 --directory docs

Then open http://localhost:8000/.

GitHub Pages deployment

The included workflow publishes docs/. In repository settings, choose GitHub Actions as the Pages source. The site URL is:

https://datascienceuibk.github.io/RETECO/

Important dates

  • Sample data: August 8, 2026
  • Training data: September 1, 2026
  • Evaluation: January 10–31, 2027
  • Paper and workshop dates: tentative; see the official SemEval-2027 calendar

Organizers

Abdelrahman Abdallah, Mohammed Ali, Muhammad Abdul-Mageed, Kevin Duh, and Adam Jatowt.

For task questions, contact Abdelrahman Abdallah.

License

The SemEval data release is planned under CC BY 4.0. Existing benchmark data and code may use different licenses; consult the license attached to each resource. A repository-level software license will be added before the first RETECO code release.

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