README.md

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YAML tags:
  - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging

Dataset Card for [Dataset Name]

Table of Contents

• Dataset Card for [Dataset Name]
  • Table of Contents
  • Dataset Description
    • Dataset Summary
    • Supported Tasks and Leaderboards
    • Languages
  • Dataset Structure
    • Data Instances
    • Data Fields
    • Data Splits
  • Dataset Creation
    • Curation Rationale
    • Source Data
      • Initial Data Collection and Normalization
      • Who are the source language producers?
    • Annotations
      • Annotation process
      • Who are the annotators?
    • Personal and Sensitive Information
  • Considerations for Using the Data
    • Social Impact of Dataset
    • Discussion of Biases
    • Other Known Limitations
  • Additional Information
    • Dataset Curators
    • Licensing Information
    • Citation Information
    • Contributions

Dataset Description

• Homepage:
• Repository:
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

This dataset is based on the content of the SourceData (https://sourcedata.embo.org) database, which contains manually annotated figure legends written in English and extracted from scientific papers in the domain of cell and molecular biology (Liechti et al, Nature Methods, 2017, https://doi.org/10.1038/nmeth.4471). The dataset was built to train models for the automatic extraction of a knowledge graph based from the scientific literature. The dataset can be used to train models for text segmentation, named entity recognition and semantic role labeling. The dataset is pre-tokenized with the roberta-base tokenizer.

Supported Tasks and Leaderboards

Tags are provided as IOB2-style tags.

PANELIZATION: figure captions (or figure legends) are usually composed of segments that each refer to one of several 'panels' of the full figure. Panels tend to represent results obtained with a coherent method and depicts data points that can be meaningfully compared to each other. PANELIZATION provide the start (B-PANEL_START) of these segments and allow to train for recogntion of the boundary between consecutive panel lengends.

NER: biological and chemical entities are labeled. Specifically the following entities are tagged:

• SMALL_MOLECULE: small molecules
• GENEPROD: gene products (genes and proteins)
• SUBCELLULAR: subcellular components
• CELL: cell types and cell lines.
• TISSUE: tissues and organs
• ORGANISM: species
• EXP_ASSAY: experimental assays

ROLES: the role of entities with regard to the causal hypotheses tested in the reported results. The tags are:

• CONTROLLED_VAR: entities that are associated with experimental variables and that subjected to controlled and targeted perturbations.
• MEASURED_VAR: entities that are associated with the variables measured and the object of the measurements.

BORING: entities are marked with the tag BORING when they are more of descriptive value and not directly associated with causal hypotheses ('boring' is not an ideal choice of word, but it is short...). Typically, these entities are so-called 'reporter' geneproducts, entities used as common baseline across samples, or specify the context of the experiment (cellular system, species, etc...).

Languages

The text in the dataset is English.

Dataset Structure

Data Instances

[More Information Needed]

Data Fields

• tokens:
• input_ids:
• label_ids:
  • entity_types:
  • geneprod_roles:
  • boring:
  • panel_start:

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

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

Thanks to @github-username for adding this dataset.