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license: mit
language:
- en
- de
- fr
- it
- es
- pt
- hy
- ka
- ne
- sr
- zh
- fil
- nl
pretty_name: "LEGEX Goldensets: Expert-Coded Review-Table Annotations"
size_categories:
- 1K<n<10K
task_categories:
- text-classification
- token-classification
- text-generation
tags:
- legal
- benchmark
- civil-judgments
- information-extraction
- llm-evaluation
- cross-jurisdictional
dataset_info:
- config_name: default
features:
- name: case_id
dtype: string
- name: link
dtype: string
- name: full_text
dtype: string
- name: legal_subject_judgement
dtype: string
- name: trial_start_date
dtype: date32
- name: trial_end_date
dtype: date32
- name: dispute_value_nominal
dtype: string
- name: Currency_dispute_value_nominal
dtype: string
- name: plaintiff_loosing_share
dtype: float64
- name: court_cost_awarded_nominal
dtype: float64
- name: Currency_court_cost_awarded_nominal
dtype: string
- name: party_compensation_awarded_nominal
dtype: float64
- name: Currency_party_compensation_awarded_nominal
dtype: string
- name: plaintiffs_all_count
dtype: int64
- name: defendants_all_count
dtype: int64
- name: plaintiff_no1_ISIC1_industry_category
dtype: string
- name: defendant_no1_ISIC1_industry_category
dtype: string
- name: comment
dtype: string
- name: original_input
dtype: string
- name: annotator_id
dtype: string
configs:
- config_name: default
data_files:
- split: armenia
path: data/am/goldenset_am.jsonl
- split: australia
path: data/au/goldenset_au.jsonl
- split: belgium
path: data/be/goldenset_be.jsonl
- split: brazil
path: data/br/goldenset_br.jsonl
- split: france
path: data/fr/goldenset_fr.jsonl
- split: georgia
path: data/ge/goldenset_ge.jsonl
- split: germany
path: data/de/goldenset_de.jsonl
- split: hong_kong
path: data/hk/goldenset_hk.jsonl
- split: india
path: data/in/goldenset_in.jsonl
- split: nepal
path: data/np/goldenset_np.jsonl
- split: new_zealand
path: data/nz/goldenset_nz.jsonl
- split: philippines
path: data/ph/goldenset_ph.jsonl
- split: serbia
path: data/rs/goldenset_rs.jsonl
- split: singapore
path: data/sg/goldenset_sg.jsonl
- split: spain
path: data/es/goldenset_es.jsonl
- split: switzerland
path: data/ch/goldenset_ch.jsonl
- split: taiwan
path: data/tw/goldenset_tw.jsonl
- split: united_kingdom
path: data/uk/goldenset_uk.jsonl
- split: united_states
path: data/us/goldenset_us.jsonl
---
# LEGEX Goldensets: Expert-Coded Review-Table Annotations
This repository contains the expert-coded gold annotations for the LEGEX
benchmark of civil-judgment review-table extraction. 1,548 judgments across
19 jurisdictions have been annotated by hand against a shared 14-field schema
covering monetary outcomes, cost allocation, party structure, and industry
classification. Including independent secondary re-annotations, the release
holds 1,974 annotation rows.
## Dataset summary
Legal review-table systems are increasingly used to extract structured facts
from judgments, but there is little public evidence on their reliability in
cross-jurisdictional legal settings. LEGEX is an expert-coded benchmark for
civil-judgment review-table extraction. The current release contains an
eight-jurisdiction core benchmark with at least 100 judgments per jurisdiction,
each coded by two or more independent experts on a 28–30 case overlap and
eleven preview jurisdictions for testing schema portability. The re-annotated
overlap enables inter-annotator agreement (IAA) analysis on the core set.
The word cloud below shows the topical spread of the free-text
`legal_subject_judgement` labels over all annotated judgments (underscores
stripped, stopwords and generic terms such as "law" removed):
## Schema
Each line in `data/<cc>/goldenset_<cc>.jsonl` is a JSON object with these
keys:
| Key | Type | Description |
|-----|-----|---------------------------------------------------------------------------------------------------------------------------------|
| `case_id` | string | Identifier within the source database. |
| `link` | string | URL to the original judgment. |
| `full_text` | string \| null | Full judgment text used as model input. |
| `legal_subject_judgement` | string | Short English subject of the case. Acts as the "this row has been substantively reviewed" marker. |
| `trial_start_date` | YYYY-MM-DD \| null | Trial start date. |
| `trial_end_date` | YYYY-MM-DD \| null | Decision date. |
| `dispute_value_nominal` | string \| null | Amount in dispute as a string (e.g. `"150000"`) or the literal `"nonpecuniary"`. |
| `Currency_dispute_value_nominal` | string \| null | ISO-4217 currency code. |
| `plaintiff_loosing_share` | number [0, 1] \| null | Plaintiff's losing share. |
| `court_cost_awarded_nominal` | number \| null | Court fees awarded. |
| `Currency_court_cost_awarded_nominal` | string \| null | ISO-4217 currency code. |
| `party_compensation_awarded_nominal` | number \| null | Party compensation awarded. |
| `Currency_party_compensation_awarded_nominal` | string \| null | ISO-4217 currency code. |
| `plaintiffs_all_count` | integer \| null | Number of plaintiffs. |
| `defendants_all_count` | integer \| null | Number of defendants. |
| `plaintiff_no1_ISIC1_industry_category` | string \| null | ISIC Section A–U for the first plaintiff. |
| `defendant_no1_ISIC1_industry_category` | string \| null | ISIC Section A–U for the first defendant. |
A row is included when `legal_subject_judgement` is populated (the marker the
annotator used to flag a row as substantively reviewed). Cells left empty by
the annotator are stored as `null`. In the raw JSONL the trial dates are
`YYYY-MM-DD` strings. The declared dataset features type them as `date32`, so
the `datasets` library returns them as date objects.
### Traceability fields
Every record additionally carries provenance fields so each value is
auditable:
| Key | Type | Description |
|-----|-----|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `annotator_id` | string | Pseudonymous, salted-hash id of the coder, stable per person across jurisdictions. |
| `comment` | string \| null | Human-readable note listing every field changed during sanitization, e.g. `"The trial_end_date was sanitized from '2026_03_19' to '2026-03-19'."`, `null` when the record needed no change. |
| `original_input` | string | JSON object mapping each changed field to its 1:1 pre-sanitization value, `"{}"` when nothing changed. This lets any consumer reconstruct the raw value. |
### Primary and secondary annotations
Jurisdictions that received an independent re-annotation contain both the
primary annotator's rows and the secondary annotators' rows, distinguished by
`annotator_id`. Within each file all primary rows come first and re-annotation
rows are appended after them, so **the first row per `case_id` is the primary
gold annotation**. For benchmark evaluation, deduplicate to the primary rows.
For inter-annotator agreement, group the duplicated `case_id`s by
`annotator_id`.
## Jurisdictions
### Highest civil court per jurisdiction
| Jurisdiction | Highest court (civil jurisdiction) | Language(s) |
|-----|-----|-----|
| Armenia | Court of Cassation (Civil Chamber) | Armenian |
| Australia | High Court of Australia | English |
| Belgium | Cour de cassation / Hof van Cassatie | French, Dutch |
| Brazil | Superior Tribunal de Justiça | Portuguese |
| France | Cour de cassation | French |
| Georgia | Supreme Court of Georgia | Georgian |
| Germany | Bundesgerichtshof | German |
| Hong Kong | Court of Final Appeal | English, Chinese |
| India | Supreme Court of India | English |
| Nepal | Supreme Court of Nepal | Nepali |
| New Zealand | Court of Appeal / High Court | English |
| Philippines | Supreme Court of the Philippines | English, Filipino |
| Serbia | Supreme Court of Cassation | Serbian |
| Singapore | Supreme Court (incl. SICC) | English |
| Spain | Tribunal Supremo (Sala de lo Civil) | Spanish |
| Switzerland | Federal Supreme Court | German, French, Italian |
| Taiwan | Supreme Court | Chinese |
| United Kingdom | Supreme Court of the United Kingdom | English |
| United States | Supreme Court of the United States | English |
### Data sources, judgment counts and annotation rows
`# judgments` counts unique expert-coded cases, `# rows` additionally counts
independent secondary re-annotations of the same cases.
| Jurisdiction | Data source | Time span | # judgments | # rows | Annotators |
|-----|-----|-----|-----|-----|-----|
| Armenia | [cassationcourt.am](https://www.cassationcourt.am) | 2024 – 2026 | 58 | 58 | 1 |
| Australia | [HF isaacus/high-court-of-australia-cases](https://huggingface.co/datasets/isaacus/high-court-of-australia-cases) | 2015 – 2025 | 30 | 30 | 1 |
| Belgium | [juportal.be](https://juportal.be) | 2015 – 2025 | 55 | 55 | 1 |
| Brazil | [scon.stj.jus.br](https://scon.stj.jus.br) | 2002 – 2026 | 130 | 179 | 3 |
| France | [Judilibre (PISTE) API](https://api.piste.gouv.fr/cassation/judilibre) | 2015 – 2025 | 30 | 30 | 1 |
| Georgia | [supremecourt.ge](https://www.supremecourt.ge) | 2026 only | 112 | 161 | 3 |
| Germany | [HF openlegaldata/court-decisions-germany](https://huggingface.co/datasets/openlegaldata/court-decisions-germany) | 2015 – 2022 | 130 | 180 | 3 |
| Hong Kong | [legalref.judiciary.hk](https://legalref.judiciary.hk) | 2015 – 2026 | 10 | 10 | 1 |
| India | [AWS Open Data Indian Supreme Court](https://registry.opendata.aws/indian-supreme-court-judgments) | 2017 – 2023 | 24 | 24 | 1 |
| Nepal | [nkp.gov.np](https://nkp.gov.np) | 2021 – 2025 | 130 | 130 | 1 |
| New Zealand | [justice.govt.nz JDO API](https://www.justice.govt.nz/jdo-search-api) | 2015 – 2025 | 29 | 29 | 1 |
| Philippines | [elibrary.judiciary.gov.ph](https://elibrary.judiciary.gov.ph) | 2024 – 2025 | 10 | 10 | 1 |
| Serbia | [vrh.sud.rs](https://vrh.sud.rs) | 2023 – 2025 | 26 | 26 | 1 |
| Singapore | [sgcaselaw.com](https://sgcaselaw.com) | 2025 – 2026 | 124 | 172 | 3 |
| Spain | [poderjudicial.es](https://www.poderjudicial.es) | 2025 – 2026 | 130 | 130 | 1 |
| Switzerland | [HF voilaj/swiss-caselaw](https://huggingface.co/datasets/voilaj/swiss-caselaw) | 2024 – 2025 | 130 | 190 | 3 |
| Taiwan | [judgment.judicial.gov.tw](https://judgment.judicial.gov.tw) | 2026 only | 130 | 180 | 3 |
| United Kingdom | [caselaw.nationalarchives.gov.uk](https://caselaw.nationalarchives.gov.uk) | 2015 – 2025 | 130 | 190 | 3 |
| United States | [HF free-law/Caselaw_Access_Project](https://huggingface.co/datasets/free-law/Caselaw_Access_Project) | 2020 – 2026 | 130 | 190 | 3 |
Total: 1,548 expert-coded judgments, 1,974 annotation rows.
Core benchmark (≥ 100 expert-coded judgments, coded by ≥ 2 independent
annotators): Brazil, Georgia, Germany, Singapore, Switzerland, Taiwan,
United Kingdom, United States. In each core jurisdiction 28–30 cases were
independently re-annotated by one or two additional experts.
Preview jurisdictions: the remaining eleven (Armenia, Australia, Belgium,
France, Hong Kong, India, Nepal, New Zealand, Philippines, Serbia, Spain).
Nepal reaches 130 cases but is single-annotated and therefore remains
preview.
## Loading
```python
from datasets import load_dataset
# Single jurisdiction
ds = load_dataset("legexbenchmark/goldensets", split="switzerland")
ds = load_dataset("legexbenchmark/goldensets", split="united_states")
# All jurisdictions
from datasets import concatenate_datasets
splits = [
"armenia", "australia", "belgium", "brazil", "france", "georgia",
"germany", "hong_kong", "india", "nepal", "new_zealand", "philippines",
"serbia", "singapore", "spain", "switzerland", "taiwan",
"united_kingdom", "united_states",
]
all_rows = concatenate_datasets([
load_dataset("legexbenchmark/goldensets", split=s) for s in splits
])
```
## Limitations
- Sample sizes: Nine of the nineteen jurisdictions have fewer than 100
expert-coded judgments; Nepal and Spain reach 100+ cases but are
single-annotated. These eleven are marked as preview and intended for
schema-portability checks rather than per-jurisdiction performance claims.
- Time coverage: Source databases vary considerably (Georgia and Taiwan are
2026-only because earlier years were not freely available).
- Schema portability: the 14 fields were designed against civil judgments
in common-law and Western European civil-law systems. Some fields
(e.g. `plaintiff_loosing_share`, ISIC categorisation) may not be a natural
fit for every jurisdiction.
- Court selection: For Brazil, there are judgements that are not from the
highest possible court. This can be inferred with the case id. The Spain
goldenset draws mainly on the Tribunal Constitucional and the Tribunal
Económico-Administrativo Central rather than the Tribunal Supremo (Sala de
lo Civil); the court can likewise be inferred from the case_id.
- Full-text quality: Text was extracted from heterogeneous sources (HTML,
PDF, API JSON). Layout artefacts and OCR errors are possible.
## Citation
Anonymous submission to the ICML 2026 AI for Law workshop. Citation block
will be added after the camera-ready release.
## License
MIT.
|