README.md

metadata

license: cc-by-nc-sa-4.0
task_categories:
  - text-classification
  - token-classification
language:
  - en
multilinguality:
  - monolingual
size_categories:
  - n<1K
tags:
  - causality
pretty_name: BioCause
configs:
  - config_name: causality detection
    data_files:
      - split: train
        path: causality-detection/train.parquet
      - split: validation
        path: causality-detection/dev.parquet
      - split: test
        path: causality-detection/test.parquet
    features:
      - name: index
        dtype: string
      - name: text
        dtype: string
      - name: label
        dtype:
          class_label:
            names:
              '0': uncausal
              '1': causal
  - config_name: causal candidate extraction
    data_files:
      - split: train
        path: causal-candidate-extraction/train.parquet
      - split: validation
        path: causal-candidate-extraction/dev.parquet
      - split: test
        path: causal-candidate-extraction/test.parquet
    features:
      - name: index
        dtype: string
      - name: text
        dtype: string
      - name: entity
        sequence:
          sequence: int32
  - config_name: causality identification
    data_files:
      - split: train
        path: causality-identification/train.parquet
      - split: validation
        path: causality-identification/dev.parquet
      - split: test
        path: causality-identification/test.parquet
    features:
      - name: index
        dtype: string
      - name: text
        dtype: string
      - name: relations
        list:
          - name: relationship
            dtype:
              class_label:
                names:
                  '0': no-rel
                  '1': causal
          - name: first
            dtype: string
          - name: second
            dtype: string
train-eval-index:
  - config: causality detection
    task: text-classification
    task_id: text_classification
    splits:
      train_split: train
      eval_split: test
    col_mapping:
      text: text
      label: label
    metrics:
      - type: accuracy
      - type: precision
      - type: recall
      - type: f1
  - config: causal candidate extraction
    task: token-classification
    task_id: token_classification
    splits:
      train_split: train
      eval_split: test
    metrics:
      - type: accuracy
      - type: precision
      - type: recall
      - type: f1
  - config: causality identification
    task: text-classification
    task_id: text_classification
    splits:
      train_split: train
      eval_split: test
    metrics:
      - type: accuracy
      - type: precision
      - type: recall
      - type: f1

This repository integrates the BioCause corpus into hf datasets. Please find the original dataset here. The data is sourced from the CREST aggregation. Please see the citations at the end of this README.

Dataset Description

• Homepage: https://github.com/Luisiglm/BioCause
• Paper: BioCause: Annotating and Analysing Causality in the Biomedical Domain

Usage

Causality Detection

from datasets import load_dataset
dataset = load_dataset("thagen/BioCause", "causality detection")

Causal Candidate Extraction

from datasets import load_dataset
dataset = load_dataset("thagen/BioCause", "causal candidate extraction")

Causality Identification

from datasets import load_dataset
dataset = load_dataset("thagen/BioCause", "causality identification")

Citations

The BioCause paper by Mihaila et al., 2013:

@article{mihaila:2013,
  title = {{{BioCause}}: {{Annotating}} and Analysing Causality in the Biomedical Domain},
  shorttitle = {{{BioCause}}},
  author = {Mihaila, Claudiu and Ohta, Tomoko and Pyysalo, Sampo and Ananiadou, Sophia},
  year = {2013},
  journal = {BMC Bioinform.},
  volume = {14},
  pages = {2},
  doi = {10.1186/1471-2105-14-2}
}

CREST by Hosseini et al., 2021 — whose aggregation we used to source the BioCause data:

@article{hosseini:2021,
  title = {Predicting {{Directionality}} in {{Causal Relations}} in {{Text}}},
  author = {Hosseini, Pedram and Broniatowski, David A. and Diab, Mona T.},
  year = {2021},
  journal = {CoRR},
  volume = {abs/2103.13606},
  eprint = {2103.13606},
  archiveprefix = {arXiv}
}