A dataset of Spanish financial annual report paragraphs from 2014 to 2018, annotated for causality detection. The data was created for the FinCausal 2023 shared task, with linguists labeling cause and effect elements within each paragraph. It is published by e-cienciaDatos Harvested Dataverse and was last updated in October 2025.
Use Cases
- Fine-tuning language models for financial causality detection based on annotated cause-effect pairs.
- Benchmarking NLP systems on a Spanish-language financial text task.
- Studying linguistic patterns of causality in corporate annual reports.
Strengths
- Data is annotated by linguists with inter-annotator agreement, suggesting quality labels.
- Source documents are Spanish financial annual reports from a defined 2014-2018 period.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count and dataset size are unknown, which may limit suitability assessment.
Provenance
- Source
- Corpus of Spanish financial annual reports.
- Collection Method
- Extracted and annotated for the FinCausal 2023 shared task.
- Time Range
- 2014 to 2018
- Freshness
- Last updated 2025-10-14 21:27:51; freshness should be verified.
- Geography
- null