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Datasets:
tner
/
bionlp2004

Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
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10K - 100K
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tokens
sequence
tags
sequence
[ "Since", "HUVECs", "released", "superoxide", "anions", "in", "response", "to", "TNF", ",", "and", "H2O2", "induces", "VCAM-1", ",", "PDTC", "may", "act", "as", "a", "radical", "scavenger", "." ]
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[ "Although", "ICAM-1", "induction", "was", "unaffected", ",", "inhibitors", "of", "NADPH", "oxidase", "(", "apocynin", ")", "or", "cytochrome", "P-450", "(", "SKF525a", ")", "suppressed", "VCAM-1", "induction", "by", "TNF", ",", "revealing", "that", "several", "radical-generating", "systems", "are", "involved", "in", "its", "regulation", "." ]
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[ "PDTC", ",", "apocynin", ",", "or", "SKF525a", "decreased", "adhesion", "of", "monocytic", "U937", "cells", "to", "TNF-treated", "HUVECs", "(", "by", "75", "%", "at", "100", "mumol/L", "PDTC", ")", "." ]
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[ "Inhibition", "by", "anti-VCAM-1", "monoclonal", "antibody", "1G11", "indicated", "that", "U937", "adhesion", "was", "VCAM-1", "dependent", "and", "suppression", "by", "antioxidants", "was", "due", "to", "reduced", "VCAM-1", "induction", "." ]
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[ "(", "ABSTRACT", "TRUNCATED", "AT", "250", "WORDS", ")" ]
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[ "Displacement", "of", "an", "E-box-binding", "repressor", "by", "basic", "helix-loop-helix", "proteins", ":", "implications", "for", "B-cell", "specificity", "of", "the", "immunoglobulin", "heavy-chain", "enhancer", "." ]
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[ "The", "activity", "of", "the", "immunoglobulin", "heavy-chain", "(", "IgH", ")", "enhancer", "is", "restricted", "to", "B", "cells", ",", "although", "it", "binds", "both", "B-cell-restricted", "and", "ubiquitous", "transcription", "factors", "." ]
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[ "Activation", "of", "the", "enhancer", "in", "non-B", "cells", "upon", "overexpression", "of", "the", "basic", "helix-loop-helix", "(", "bHLH", ")", "protein", "E2A", "appears", "to", "be", "mediated", "not", "only", "by", "the", "binding", "of", "E2A", "to", "its", "cognate", "E", "box", "but", "also", "by", "the", "resulting", "displacement", "of", "a", "repressor", "from", "that", "same", "site", "." ]
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[ "We", "have", "identified", "a", "``", "two-handed", "''", "zinc", "finger", "protein", ",", "denoted", "ZEB", ",", "the", "DNA-binding", "specificity", "of", "which", "mimics", "that", "of", "the", "cellular", "repressor", "." ]
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[ "By", "employing", "a", "derivative", "E", "box", "that", "binds", "ZEB", "but", "not", "E2A", ",", "we", "have", "shown", "that", "the", "repressor", "is", "active", "in", "B", "cells", "and", "the", "IgH", "enhancer", "is", "silenced", "in", "the", "absence", "of", "binding", "competition", "by", "bHLH", "proteins", "." ]
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[ "Hence", ",", "we", "propose", "that", "a", "necessary", "prerequisite", "of", "enhancer", "activity", "is", "the", "B-cell-specific", "displacement", "of", "a", "ZEB-like", "repressor", "by", "bHLH", "proteins", "." ]
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[ "Inhibition", "of", "NF-kappa", "B", "by", "sodium", "salicylate", "and", "aspirin", "[", "see", "comments", "]" ]
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[ "The", "transcription", "factor", "nuclear", "factor-kappa", "B", "(", "NF-kappa", "B", ")", "is", "critical", "for", "the", "inducible", "expression", "of", "multiple", "cellular", "and", "viral", "genes", "involved", "in", "inflammation", "and", "infection", "including", "interleukin-1", "(", "IL-1", ")", ",", "IL-6", ",", "and", "adhesion", "molecules", "." ]
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[ "The", "anti-inflammatory", "drugs", "sodium", "salicylate", "and", "aspirin", "inhibited", "the", "activation", "of", "NF-kappa", "B", ",", "which", "further", "explains", "the", "mechanism", "of", "action", "of", "these", "drugs", "." ]
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[ "This", "inhibition", "prevented", "the", "degradation", "of", "the", "NF-kappa", "B", "inhibitor", ",", "I", "kappa", "B", ",", "and", "therefore", "NF-kappa", "B", "was", "retained", "in", "the", "cytosol", "." ]
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[ "Sodium", "salicylate", "and", "aspirin", "also", "inhibited", "NF-kappa", "B", "-dependent", "transcription", "from", "the", "Ig", "kappa", "enhancer", "and", "the", "human", "immunodeficiency", "virus", "(", "HIV", ")", "long", "terminal", "repeat", "(", "LTR", ")", "in", "transfected", "T", "cells", "." ]
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[ "Effects", "of", "the", "antisense", "myb", "expression", "on", "hemin-", "and", "erythropoietin-", "induced", "erythroid", "differentiation", "of", "K562", "cells", "." ]
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[ "During", "treatment", "with", "Hm", ",", "K562", "cells", "constitutively", "expressed", "c-myb", "mRNA", ",", "and", "50", "%", "of", "them", "began", "to", "synthesize", "hemoglobin", "(", "Hb", ")", "." ]
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[ "Expression", "of", "antisense", "myb", "RNA", "reduced", "the", "amount", "of", "c-myb", "mRNA", ",", "and", "the", "percentage", "of", "Hb-synthesizing", "cells", "was", "decreased", "to", "20", "%", "." ]
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[ "Expression", "of", "GATA-1", "mRNA", "was", "almost", "constant", "during", "Hm", "-induced", "differentiation", ",", "but", "increased", "during", "Epo", "treatment", "." ]
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[ "Prenatal", "immune", "challenge", "alters", "the", "hypothalamic-pituitary-adrenocortical", "axis", "in", "adult", "rats", "." ]
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[ "We", "investigated", "whether", "non-abortive", "maternal", "infections", "would", "compromise", "fetal", "brain", "development", "and", "alter", "hypothalamic-pituitary-adrenocortical", "(", "HPA", ")", "axis", "functioning", "when", "adult", "." ]
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[ "To", "study", "putative", "teratogenic", "effects", "of", "a", "T", "cell-mediated", "immune", "response", "versus", "an", "endotoxic", "challenge", ",", "10-d-pregnant", "rats", "received", "a", "single", "intraperitoneal", "injection", "of", "5", "x", "10", "(", "8", ")", "human", "red", "blood", "cells", "(", "HRBC", ")", "or", "gram-negative", "bacterial", "endotoxin", "(", "Escherichia", "coli", "LPS", ":", "30", "micrograms/kg", ")", "." ]
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[ "The", "adult", "male", "progeny", "(", "3", "mo", "old", ")", "of", "both", "experimental", "groups", "showed", "increased", "basal", "plasma", "corticosterone", "levels", "." ]
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End of preview. Expand in Dataset Viewer.

Dataset Card for "tner/bionlp2004"

Dataset Summary

BioNLP2004 NER dataset formatted in a part of TNER project. BioNLP2004 dataset contains training and test only, so we randomly sample a half size of test instances from the training set to create validation set.

  • Entity Types: DNA, protein, cell_type, cell_line, RNA

Dataset Structure

Data Instances

An example of train looks as follows.

{
    'tags': [0, 0, 0, 0, 3, 0, 9, 10, 0, 0, 0, 0, 0, 7, 8, 0, 3, 0, 0, 9, 10, 10, 0, 0],
    'tokens': ['In', 'the', 'presence', 'of', 'Epo', ',', 'c-myb', 'mRNA', 'declined', 'and', '20', '%', 'of', 'K562', 'cells', 'synthesized', 'Hb', 'regardless', 'of', 'antisense', 'myb', 'RNA', 'expression', '.']
}

Label ID

The label2id dictionary can be found at here.

{
    "O": 0,
    "B-DNA": 1,
    "I-DNA": 2,
    "B-protein": 3,
    "I-protein": 4,
    "B-cell_type": 5,
    "I-cell_type": 6,
    "B-cell_line": 7,
    "I-cell_line": 8,
    "B-RNA": 9,
    "I-RNA": 10
}

Data Splits

name train validation test
bionlp2004 16619 1927 3856

Citation Information 

@inproceedings{collier-kim-2004-introduction,
    title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}",
    author = "Collier, Nigel  and
      Kim, Jin-Dong",
    booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B}io{NLP})",
    month = aug # " 28th and 29th",
    year = "2004",
    address = "Geneva, Switzerland",
    publisher = "COLING",
    url = "https://aclanthology.org/W04-1213",
    pages = "73--78",
}
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Repository:
T-NER
Paper:
aclanthology.org
Dataset:
BioNLP2004
Domain:
Biochemical
Number of Entity:
5
Size of downloaded dataset files:
7.76 MB
Size of the auto-converted Parquet files:
1.87 MB
Number of rows:
22,402

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