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Datasets:
tner
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fin

Tasks:
Token Classification
Sub-tasks: named-entity-recognition
Languages: English
Multilinguality: monolingual
Size Categories: 1K<n<10K
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tokens
sequence
tags
sequence
[ "(", "l", ")", "\"", "Tranche", "A", "Shares", "\"", "has", "the", "meaning", "as", "defined", "in", "the", "Subscription", "Agreement", "." ]
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[ "(", "m", ")", "\"", "Tranche", "B", "Cash", "Payment", "\"", "has", "the", "meaning", "as", "defined", "in", "the", "Subscription", "Agreement", "." ]
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[ "(", "n", ")", "\"", "USD", "\"", "means", "US", "dollars", ",", "the", "lawful", "currency", "of", "the", "United", "State", "of", "America", "." ]
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[ "1", ".", "2", "Other", "Terms", "Other", "terms", "may", "be", "defined", "elsewhere", "in", "the", "text", "of", "this", "Agreement", "and", ",", "unless", "otherwise", "indicated", ",", "shall", "have", "such", "meaning", "indicated", "throughout", "this", "Agreement", "." ]
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[ "Article", "2", "Loan" ]
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[ "2", ".", "2", "Grant", "of", "the", "Loan" ]
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Dataset Card for "tner/fin"

Dataset Summary

FIN NER dataset formatted in a part of TNER project. FIN dataset contains training (FIN5) and test (FIN3) only, so we randomly sample a half size of test instances from the training set to create validation set.

  • Entity Types: ORG, LOC, PER, MISC

Dataset Structure

Data Instances

An example of train looks as follows.

{
    "tags": [0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
    "tokens": ["1", ".", "1", ".", "4", "Borrower", "engages", "in", "criminal", "conduct", "or", "is", "involved", "in", "criminal", "activities", ";"]
}

Label ID

The label2id dictionary can be found at here.

{
  "O": 0,
  "B-PER": 1,
  "B-LOC": 2,
  "B-ORG": 3,
  "B-MISC": 4,
  "I-PER": 5,
  "I-LOC": 6,
  "I-ORG": 7,
  "I-MISC": 8
}

Data Splits

name train validation test
fin 1014 303 150

Citation Information 

@inproceedings{salinas-alvarado-etal-2015-domain,
    title = "Domain Adaption of Named Entity Recognition to Support Credit Risk Assessment",
    author = "Salinas Alvarado, Julio Cesar  and
      Verspoor, Karin  and
      Baldwin, Timothy",
    booktitle = "Proceedings of the Australasian Language Technology Association Workshop 2015",
    month = dec,
    year = "2015",
    address = "Parramatta, Australia",
    url = "https://aclanthology.org/U15-1010",
    pages = "84--90",
}
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Edit dataset card
Repository:
T-NER
Paper:
aclanthology.org
Dataset:
FIN
Domain:
Financial News
Number of Entity:
4
Size of downloaded dataset files:
652 kB
Size of the auto-converted Parquet files:
134 kB
Number of rows:
1,473

Models trained or fine-tuned on tner/fin