Mention counts below measure name matches in tracked papers, not benchmark quality or downloads. A family count can cover multiple datasets; it is not a separate count for each comparison row. Choose a task and version first, preserve evaluation splits, and follow the linked release terms. The site's content license does not replace the datasets' own terms.
NLP dataset comparison: tasks, access and usage conditions
Dataset / version
Task and evaluation
Access and preparation
Usage conditions
CoNLL-2003 NER
Token-level named-entity recognition: person, organization, location and miscellaneous.
Evaluation: Entity-span F1 using the prescribed evaluation; token accuracy is not an equivalent metric.
The shared-task paper documents the annotation format. Obtain source Reuters text through NIST and follow the task preparation instructions; the legacy task website may be unavailable.
Shared-task annotations and source news text have distinct conditions; English Reuters text access follows the applicable corpus agreement.
From Nov 2023 to Oct 2026, 118 archived papers mentioned CoNLL in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Jul 2024 (7).
No paper of the tracked journals mentioned CoNLL in the last 30 days (2026-10-06 to 2026-11-04).
From 2017 to 2026 (so far), CoNLL was mentioned in 127 papers in the tracked journals, most of them in AI (109), higher education and research (7) and operations research (4).
37 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Centre National de la Recherche Scientifique (5), Jožef Stefan Institute (5) and Jožef Stefan International Postgraduate School (5).
The journals publishing most of them were Language Resources and Evaluation (20), Artificial Intelligence Review (16) and Knowledge-Based Systems (9).
The most-cited of them is “A survey on few-shot class-incremental learning” (Neural Networks, 2023), with 221 citations.
Papers use CoNLL most often with Wikipedia (49), Hugging Face Hub (35) and Twitter / X (35); it has 24 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok.
Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.
Papers use CoNLL most often with Wikipedia (49), Hugging Face Hub (35) and Twitter / X (35); it has 24 partners in the code and data network, in the group around Twitter / X, Facebook, YouTube / TikTok. The whole network →
What papers use CoNLL together with (at least 3 papers; lift 1 = chance)
Scholar4AI. (2026). CoNLL. Journal and Conference Research Rankings. Retrieved November 4, 2026, from https://scholar4ai.com/datasets/conll
@misc{scholar4ai-datasets-conll,
author = {{Scholar4AI}},
title = {CoNLL},
year = {2026},
howpublished = {\url{https://scholar4ai.com/datasets/conll}},
urldate = {2026-11-04},
note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).