Datasets:
license: cc-by-4.0
task_categories:
- text-classification
language:
- en
tags:
- Text Classification
- Named Entity Recognition
- Structured Extraction
- Legal NLP
- International Law
IntLawNER is an English-language named entity recognition dataset for legal instrument and citation references in international-law documents. It contains 2,987 gold sentences drawn from three public legal-document collections.
Sources
| Code | Collection | Gold sentences |
|---|---|---|
CD-ICJ |
International Court of Justice | 1,045 |
ECtHR |
European Court of Human Rights | 1,149 |
UNSC |
UN Security Council | 793 |
The raw source documents are not bundled. Collection URLs and acquisition
metadata are recorded in data/corpus_manifest.json. Document provenance is
retained in each record's corpus and doc_id fields.
Annotation Schema
Each line is a JSON object. Core fields are:
{
"sent_id": "stable sentence identifier",
"text": "sentence text",
"corpus": "CD-ICJ, ECtHR, or UNSC",
"doc_id": "source document identifier",
"label": [
{
"start": 0,
"end": 10,
"text": "exact span",
"labels": ["IL_PROVISION"]
}
]
}
Entity Distribution
| Label | Count |
|---|---|
IL_PROVISION |
3,026 |
IL_TREATY |
1,641 |
IL_RESOLUTION |
1,322 |
IL_DOMESTIC_LAW |
1,208 |
IL_CASE_CITATION |
622 |
IL_SOFT_LAW |
192 |
IL_COURT_INSTR |
83 |
Definitions and concise examples are provided in the main README and the
evaluation prompt glossary under src/evaluation/.
Intended Uses
- Training and evaluating legal-domain NER systems.
- Studying references among international, domestic, judicial, and soft-law instruments.
- Comparing rule-based, transformer, and prompted-LLM extraction methods.
The dataset is not legal advice and should not be used as the sole basis for a legal decision. Performance on these three collections does not establish performance on other jurisdictions, languages, document types, or time periods.
Licensing
The original annotation layer is CC BY 4.0. Source documents retain their original terms.