File size: 4,445 Bytes
5cdffd4 00c156b a4bb60e 019dd13 00c156b c3e5ba4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | ---
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.
|