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configs:
- config_name: AQMAR_ara
data_files:
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- config_name: EverestNER_nep
data_files:
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- config_name: GermEval_deu
data_files:
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data_files:
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- config_name: Japanese_GSD_jap
data_files:
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- config_name: KIND_ita
data_files:
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path: KIND/ita/test-*
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- config_name: KazNERD_kaz
data_files:
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- config_name: L3Cube_MahaNER_mar
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- config_name: MasakhaNER_2_bam
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- config_name: MasakhaNER_2_ewe
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- config_name: MasakhaNER_2_fon
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- config_name: MasakhaNER_2_mos
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- config_name: MasakhaNER_2_nya
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- config_name: MasakhaNER_2_pcm
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- config_name: MasakhaNER_2_sna
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- config_name: MasakhaNER_2_swa
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- config_name: MasakhaNER_2_tsn
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- config_name: MasakhaNER_2_twi
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- config_name: MasakhaNER_2_wol
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- config_name: MasakhaNER_2_xho
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- config_name: MasakhaNER_2_yor
data_files:
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- config_name: MasakhaNER_2_zul
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- config_name: MasakhaNER_amh
data_files:
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- split: dev
path: MasakhaNER/amh/dev-*
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- config_name: MasakhaNER_hau
data_files:
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- config_name: MasakhaNER_ibo
data_files:
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- split: dev
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- config_name: MasakhaNER_kin
data_files:
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- config_name: MasakhaNER_lug
data_files:
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- config_name: MasakhaNER_luo
data_files:
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- config_name: MasakhaNER_pcm
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- config_name: MasakhaNER_swa
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- config_name: MasakhaNER_wol
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- config_name: MasakhaNER_yor
data_files:
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path: MasakhaNER/yor/test-*
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- config_name: NEMO_SPMRL_heb
data_files:
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- split: dev
path: NEMO_SPMRL/heb/dev-*
- split: train
path: NEMO_SPMRL/heb/train-*
- config_name: NEMO_UD_heb
data_files:
- split: test
path: NEMO_UD/heb/test-*
- split: dev
path: NEMO_UD/heb/dev-*
- split: train
path: NEMO_UD/heb/train-*
- config_name: NorNE_nno
data_files:
- split: test
path: NorNE/nno/test-*
- split: dev
path: NorNE/nno/dev-*
- split: train
path: NorNE/nno/train-*
- config_name: NorNE_nob
data_files:
- split: test
path: NorNE/nob/test-*
- split: dev
path: NorNE/nob/dev-*
- split: train
path: NorNE/nob/train-*
- config_name: RONEC_ron
data_files:
- split: test
path: RONEC/ron/test-*
- split: train
path: RONEC/ron/train-*
- config_name: SLI_Galician_Corpora_glg
data_files:
- split: test
path: SLI_Galician_Corpora/glg/test-*
- split: train
path: SLI_Galician_Corpora/glg/train-*
- config_name: ThaiNNER_tha
data_files:
- split: test
path: ThaiNNER/tha/test-*
- split: train
path: ThaiNNER/tha/train-*
- config_name: TurkuNLP_fin
data_files:
- split: test
path: TurkuNLP/fin/test-*
- split: dev
path: TurkuNLP/fin/dev-*
- split: train
path: TurkuNLP/fin/train-*
- config_name: Tweebank_eng
data_files:
- split: test
path: Tweebank/eng/test-*
- split: dev
path: Tweebank/eng/dev-*
- split: train
path: Tweebank/eng/train-*
- config_name: UNER_Chinese_GSDSIMP_cmn
data_files:
- split: test
path: UNER_Chinese_GSDSIMP/cmn/test-*
- split: dev
path: UNER_Chinese_GSDSIMP/cmn/dev-*
- split: train
path: UNER_Chinese_GSDSIMP/cmn/train-*
- config_name: UNER_Chinese_GSD_cmn
data_files:
- split: test
path: UNER_Chinese_GSD/cmn/test-*
- split: dev
path: UNER_Chinese_GSD/cmn/dev-*
- split: train
path: UNER_Chinese_GSD/cmn/train-*
- config_name: UNER_English_EWT_eng
data_files:
- split: test
path: UNER_English_EWT/eng/test-*
- split: dev
path: UNER_English_EWT/eng/dev-*
- split: train
path: UNER_English_EWT/eng/train-*
- config_name: UNER_Maghrebi_Arabic_French-Arabizi_arq
data_files:
- split: test
path: UNER_Maghrebi_Arabic_French-Arabizi/arq/test-*
- split: dev
path: UNER_Maghrebi_Arabic_French-Arabizi/arq/dev-*
- split: train
path: UNER_Maghrebi_Arabic_French-Arabizi/arq/train-*
- config_name: UNER_Portuguese-Bosque_por
data_files:
- split: test
path: UNER_Portuguese-Bosque/por/test-*
- split: dev
path: UNER_Portuguese-Bosque/por/dev-*
- split: train
path: UNER_Portuguese-Bosque/por/train-*
- config_name: UNER_Slovak_SNK_slk
data_files:
- split: test
path: UNER_Slovak_SNK/slk/test-*
- split: dev
path: UNER_Slovak_SNK/slk/dev-*
- split: train
path: UNER_Slovak_SNK/slk/train-*
- config_name: UNER_Swedish_Talkbanken_swe
data_files:
- split: test
path: UNER_Swedish_Talkbanken/swe/test-*
- split: dev
path: UNER_Swedish_Talkbanken/swe/dev-*
- split: train
path: UNER_Swedish_Talkbanken/swe/train-*
- config_name: WNUT17_eng
data_files:
- split: test
path: WNUT17/eng/test-*
- split: dev
path: WNUT17/eng/dev-*
- split: train
path: WNUT17/eng/train-*
- config_name: WikiGoldSK_slk
data_files:
- split: test
path: WikiGoldSK/slk/test-*
- split: dev
path: WikiGoldSK/slk/dev-*
- split: train
path: WikiGoldSK/slk/train-*
- config_name: elNER_ell
data_files:
- split: test
path: elNER/ell/test-*
- split: dev
path: elNER/ell/dev-*
- split: train
path: elNER/ell/train-*
- config_name: hr500k_hrv
data_files:
- split: test
path: hr500k/hrv/test-*
- split: dev
path: hr500k/hrv/dev-*
- split: train
path: hr500k/hrv/train-*
- config_name: ssj500k_slv
data_files:
- split: test
path: ssj500k/slv/test-*
- split: dev
path: ssj500k/slv/dev-*
- split: train
path: ssj500k/slv/train-*
pretty_name: >-
OpenNER 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+
Languages
size_categories: 100K<n<1M
multilinguality: multilingual
language:
- ca
- es
- ar
- de
- nl
- da
- eu
- el
- ne
- hi
- hr
- ja
- kk
- it
- mr
- am
- ha
- ig
- rw
- sw
- wo
- yo
- bm
- ee
- ny
- sn
- tn
- tw
- xh
- zu
- he
- 'no'
- ro
- gl
- sl
- th
- fi
- en
- zh
- pt
- sk
- sv
task_categories:
- token-classification
license: cc-by-4.0
Dataset Card for OpenNER 1.0
OpenNER 1.0 is a standardized collection of openly-available named entity recognition (NER) datasets. OpenNER contains 36 NER corpora that span 52 languages, human-annotated in varying named entity ontologies. We correct annotation format issues, standardize the original datasets into a uniform representation with consistent entity type names across corpora, and provide the collection in a structure that enables research in multilingual and multi-ontology NER.
This version of the dataset contains all original entity types for each dataset after validation and normalization.
Dataset Details
Dataset Description
- Curated by: BLT Lab: Chester Palen-Michel, Maxwell Pickering, Maya Kruse, Jonne Sälevä, & Constantine Lignos
- Shared by: Chester Palen-Michel
- Language(s) (NLP): Akan/Twi, Algerian Arabic,Amharic, Arabic, Bambara, Basque, Bavarian German, Catalan, Chichewa, chiShona, Croatian, Danish, Dutch, English, Éwé, Finnish, Fon, Galician, German, Ghomálá', Greek, Hausa, Hebrew, Hindi, Igbo, isiXhosa, Italian, Japanese, Kazakh, Kinyarwanda, Kiswahili, Luganda, Luo, Mandarin Chinese, Marathi, Mossi, Naija, Nepali, Norwegian, Persian Farsi, Portuguese, Romanian, Setswana, Slovak, Slovenian, Spanish, Swedish, Thai, Wolof, Yoruba, Zulu,
- License: CC-BY 4.0 for the OpenNER collection. Individual datasets have their own licenses.
Dataset Sources
- Repository: OpenNER Github
- Paper: ACL Anthology and arXiv
Uses
Primarily to be used for research regarding multilingual NER with different entity sets and annotation guidelines.
Dataset Structure
{
'id': '0',
'tokens': ['Melbourne', '(', 'Australia', ')', ',', '25', 'may', '(', 'EFE', ')', '.'],
'ner_tags': [5, 0, 5, 0, 0, 0, 0, 0, 3, 0, 0]
}
The ner_tags column includes an internal int2str map to access the corresponding string label
for each integer label.
Dataset Creation
Curation Rationale
There are many NER datasets but many have different formats, label names, and label schemas. OpenNER standardizes and collects these many NER datasets in easily accessible format and place.
Source Data
OpenNER primarily contains newswire and web text. See our paper with each cited paper describing each dataset for details of source data.
Data Collection and Processing
See our paper for details on data collection and processing.
Who are the source data producers?
See our paper with each cited paper describing each dataset for details of source data.
Annotations
Annotation is named entity recognition annotation on each token in BIO format.
Annotation process
See our paper with each cited paper for each dataset for details on the annotation process.
Who are the annotators?
OpenNER is a collection of many existing datasets which have been human annotated. Annotator details are included in each dataset's original publication. Citations for each work can be found in our paper.
Personal and Sensitive Information
To the best of our knowledge there is no personal or sensitive information beyond that which generally occurs in newswire text.
Bias, Risks, and Limitations
See our paper for discussion of limitations and biases.
Recommendations
See our paper for recommendations regarding OpenNER.
Citation
If you make use of this dataset, please cite our paper using this bibtex:
BibTeX:
@inproceedings{palen-michel-etal-2025-openner,
title = "{O}pen{NER} 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+ Languages",
author = {Palen-Michel, Chester and
Pickering, Maxwell and
Kruse, Maya and
S{\"a}lev{\"a}, Jonne and
Lignos, Constantine},
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-main.1708/",
doi = "10.18653/v1/2025.emnlp-main.1708",
pages = "33637--33662",
ISBN = "979-8-89176-332-6",
abstract = "We present OpenNER 1.0, a standardized collection of openly-available named entity recognition (NER) datasets.OpenNER contains 36 NER corpora that span 52 languages, human-annotated in varying named entity ontologies.We correct annotation format issues, standardize the original datasets into a uniform representation with consistent entity type names across corpora, and provide the collection in a structure that enables research in multilingual and multi-ontology NER.We provide baseline results using three pretrained multilingual language models and two large language models to compare the performance of recent models and facilitate future research in NER.We find that no single model is best in all languages and that significant work remains to obtain high performance from LLMs on the NER task.OpenNER is released at https://github.com/bltlab/open-ner."
}
Dataset Card Authors
Chester Palen-Michel @cpalenmichel
Dataset Card Contact
Chester Palen-Michel @cpalenmichel