Datasets:

UppsalaNLP
/

swedish-causality-trial

license: cc-by-4.0
language:
  - sv
task_categories:
  - text-classification
tags:
  - causality
  - swedish
  - nlp
  - causality-detection
size_categories:
  - n<1K
source_datasets:
  - original

Swedish Causality Trial Dataset

Binary causality detection trial dataset for Swedish text with keyword-based sampling.

Dataset Description

This dataset contains Swedish sentences annotated for causality, sampled based on causal keywords (e.g., "bero på", "leda till").

Fields

keyword: The causal keyword used to sample the sentence
document: Source document ID
section: Section within the document
left_context: Preceding context sentences
target_sentence: The sentence to classify
right_context: Following context sentences
label: Binary annotation (0 = no causality, 1 = causality present) - majority vote of 3 annotators
annotator_agreement: Number of annotators who agreed with the majority label (2 or 3)

Usage

from datasets import load_dataset

dataset = load_dataset("UppsalaNLP/swedish-causality-trial")

# Access train/test splits
train = dataset["train"]
test = dataset["test"]

# Example
print(train[0]["keyword"])
print(train[0]["target_sentence"])
print(train[0]["label"])

Source

Text extracted from the SOU-corpus (Swedish Government Official Reports).

Citation

@inproceedings{durlich-etal-2022-cause,
    title = "Cause and Effect in Governmental Reports: Two Data Sets for Causality Detection in Swedish",
    author = "D{\"u}rlich, Luise and Reimann, Sebastian and Finnveden, Gustav and Nivre, Joakim and Stymne, Sara",
    booktitle = "Proceedings of the First Workshop on Natural Language Processing for Political Sciences",
    month = jun,
    year = "2022",
    address = "Marseilles, France"
}

License

This dataset is licensed under CC BY 4.0.