| --- |
| license: mit |
| task_categories: |
| - token-classification |
| language: |
| - en |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: tokens |
| sequence: string |
| - name: ner_tags |
| sequence: |
| class_label: |
| names: |
| '0': O |
| '1': B-SpecificDisease |
| '2': I-SpecificDisease |
| '3': B-Context_Error |
| '4': I-Context_Error |
| '5': B-Undefined_semantics |
| '6': I-Undefined_semantics |
| '7': B-SequenceVariant |
| '8': I-SequenceVariant |
| '9': B-c-Requires_causality |
| '10': I-c-Requires_causality |
| '11': B-CompositeMention |
| '12': I-CompositeMention |
| '13': B-OrganismTaxon |
| '14': I-OrganismTaxon |
| '15': B-Drug |
| '16': I-Drug |
| '17': B-Not_a_criteria |
| '18': I-Not_a_criteria |
| '19': B-Post-eligibility |
| '20': I-Post-eligibility |
| '21': B-Competing_trial |
| '22': I-Competing_trial |
| '23': B-Observation |
| '24': I-Observation |
| '25': B-Disease |
| '26': I-Disease |
| '27': B-Value |
| '28': I-Value |
| '29': B-Line |
| '30': I-Line |
| '31': B-Grammar_Error |
| '32': I-Grammar_Error |
| '33': B-Measurement |
| '34': I-Measurement |
| '35': B-CellLine |
| '36': I-CellLine |
| '37': B-Person |
| '38': I-Person |
| '39': B-Device |
| '40': I-Device |
| '41': B-Pregnancy_considerations |
| '42': I-Pregnancy_considerations |
| '43': B-DiseaseOrPhenotypicFeature |
| '44': I-DiseaseOrPhenotypicFeature |
| '45': B-Condition |
| '46': I-Condition |
| '47': B-Mood |
| '48': I-Mood |
| '49': B-Non-representable |
| '50': I-Non-representable |
| '51': B-Reference_point |
| '52': I-Reference_point |
| '53': B-Non-query-able |
| '54': I-Non-query-able |
| '55': B-Qualifier |
| '56': I-Qualifier |
| '57': B-DiseaseClass |
| '58': I-DiseaseClass |
| '59': B-Parsing_Error |
| '60': I-Parsing_Error |
| '61': B-Chemical |
| '62': I-Chemical |
| '63': B-Multiplier |
| '64': I-Multiplier |
| '65': B-ChemicalEntity |
| '66': I-ChemicalEntity |
| '67': B-Procedure |
| '68': I-Procedure |
| '69': B-Temporal |
| '70': I-Temporal |
| '71': B-Subjective_judgement |
| '72': I-Subjective_judgement |
| '73': B-GeneOrGeneProduct |
| '74': I-GeneOrGeneProduct |
| '75': B-Informed_consent |
| '76': I-Informed_consent |
| '77': B-Intoxication_considerations |
| '78': I-Intoxication_considerations |
| '79': B-Modifier |
| '80': I-Modifier |
| '81': B-Visit |
| '82': I-Visit |
| '83': B-Negation |
| '84': I-Negation |
| splits: |
| - name: test |
| num_bytes: 786438 |
| num_examples: 346 |
| - name: train |
| num_bytes: 10705550 |
| num_examples: 3259 |
| download_size: 2474358 |
| dataset_size: 11491988 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| --- |
| |
| ## Benchmark Merged dataset - Train |
| This dataset was generated by the Data preprocessing step of the NERFAIR workflow (More information: https://github.com/YasCoMa/ner-fair-workflow ) |
|
|
| It contains the train data of the following datasets: |
|
|
| - ncbi: Doğan, Rezarta Islamaj, Robert Leaman, and Zhiyong Lu. 2014. “NCBI Disease Corpus: A Resource for Disease Name Recognition and Concept Normalization.” Journal of Biomedical Informatics 47 (February): 1–10. |
|
|
| - bc5cdr: Li, Jiao, Yueping Sun, Robin J. Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J. Mattingly, Thomas C. Wiegers, and Zhiyong Lu. 2016. “BioCreative V CDR Task Corpus: A Resource for Chemical Disease Relation Extraction.” Database: The Journal of Biological Databases and Curation 2016 (May): baw068. |
|
|
| - biored: Luo, Ling, Po-Ting Lai, Chih-Hsuan Wei, Cecilia N. Arighi, and Zhiyong Lu. 2022. “BioRED: A Rich Biomedical Relation Extraction Dataset.” Briefings in Bioinformatics 23 (5): bbac282. |
|
|
| - chia: Kury, Fabrício, Alex Butler, Chi Yuan, Li-Heng Fu, Yingcheng Sun, Hao Liu, Ida Sim, Simona Carini, and Chunhua Weng. 2020. “Chia, a Large Annotated Corpus of Clinical Trial Eligibility Criteria.” Scientific Data 7 (1): 281. |
|
|
