Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
species_800 / README.md
albertvillanova's picture
Host data file (#4)
7ec89c5
metadata
annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
language:
  - en
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
pretty_name: species800
dataset_info:
  features:
    - name: id
      dtype: string
    - name: tokens
      sequence: string
    - name: ner_tags
      sequence:
        class_label:
          names:
            '0': O
            '1': B
            '2': I
  config_name: species_800
  splits:
    - name: train
      num_bytes: 2579096
      num_examples: 5734
    - name: validation
      num_bytes: 385756
      num_examples: 831
    - name: test
      num_bytes: 737760
      num_examples: 1631
  download_size: 18204624
  dataset_size: 3702612

Dataset Card for [Dataset Name]

Table of Contents

Dataset Description

Dataset Summary

S800 Corpus: a novel abstract-based manually annotated corpus. S800 comprises 800 PubMed abstracts in which organism mentions were identified and mapped to the corresponding NCBI Taxonomy identifiers.

To increase the corpus taxonomic mention diversity the S800 abstracts were collected by selecting 100 abstracts from the following 8 categories: bacteriology, botany, entomology, medicine, mycology, protistology, virology and zoology. S800 has been annotated with a focus at the species level; however, higher taxa mentions (such as genera, families and orders) have also been considered.

The Species-800 dataset was pre-processed and split based on the dataset of Pyysalo (https://github.com/spyysalo/s800).

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English (en).

Dataset Structure

Data Instances

{'id': '0',
 'tokens': ['Methanoregula',
  'formicica',
  'sp',
  '.',
  'nov',
  '.',
  ',',
  'a',
  'methane',
  '-',
  'producing',
  'archaeon',
  'isolated',
  'from',
  'methanogenic',
  'sludge',
  '.'],
 'ner_tags': [1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}

Data Fields

  • id: Sentence identifier.
  • tokens: Array of tokens composing a sentence.
  • ner_tags: Array of tags, where 0 indicates no species mentioned, 1 signals the first token of a species and 2 the subsequent tokens of the species.

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[More Information Needed]

Licensing Information

The species-level S800 corpus is subject to Medline restrictions.

Citation Information

Original data:

@article{pafilis2013species,
         title={The SPECIES and ORGANISMS resources for fast and accurate identification of taxonomic names in text},
         author={Pafilis, Evangelos and Frankild, Sune P and Fanini, Lucia and Faulwetter, Sarah and Pavloudi, Christina and Vasileiadou, Aikaterini and Arvanitidis, Christos and Jensen, Lars Juhl},
         journal={PloS one},
         volume={8},
         number={6},
         pages={e65390},
         year={2013},
         publisher={Public Library of Science}
}

Source data of this dataset:

@article{10.1093/bioinformatics/btz682,
    author = {Lee, Jinhyuk and Yoon, Wonjin and Kim, Sungdong and Kim, Donghyeon and Kim, Sunkyu and So, Chan Ho and Kang, Jaewoo},
    title = "{BioBERT: a pre-trained biomedical language representation model for biomedical text mining}",
    journal = {Bioinformatics},
    volume = {36},
    number = {4},
    pages = {1234-1240},
    year = {2019},
    month = {09},
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btz682},
    url = {https://doi.org/10.1093/bioinformatics/btz682},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/36/4/1234/48983216/bioinformatics\_36\_4\_1234.pdf},
}

and

https://github.com/spyysalo/s800

Contributions

Thanks to @edugp for adding this dataset.