license: apache-2.0
language:
- pl
task_categories:
- text-classification
tags:
- benchmark
- decision-model
- legal
- administrative
- polish
pretty_name: jerzyk-bench
size_categories:
- n<1K
annotations_creators:
- machine-generated
language_creators:
- machine-generated
- found
multilinguality:
- monolingual
configs:
- config_name: sad
default: true
data_files:
- split: test
path: data/sad_test.jsonl
- split: validation
path: data/sad_dev.jsonl
- config_name: adm
data_files:
- split: test
path: data/adm_test.jsonl
- split: validation
path: data/adm_dev.jsonl
- config_name: ksieg
data_files:
- split: test
path: data/ksieg_test.jsonl
- split: validation
path: data/ksieg_dev.jsonl
- config_name: email
data_files:
- split: test
path: data/email_test.jsonl
- split: validation
path: data/email_dev.jsonl
- config_name: sad_real
data_files:
- split: test
path: data/sad_real_test.jsonl
- split: validation
path: data/sad_real_dev.jsonl
- config_name: sad_real_fragmenty
data_files:
- split: test
path: data/sad_real_fragmenty_test.jsonl
- config_name: adm_real
data_files:
- split: test
path: data/adm_real_test.jsonl
jerzyk-bench
A Polish benchmark for decision models (typed questions with calibrated answers) on incoming correspondence: court letters, administrative notices, accounting documents and customer e-mails, plus real court rulings and real public notices.
🇵🇱 Polski benchmark modeli decyzyjnych dla korespondencji: pisma sądowe, urzędowe, księgowe i e-maile klientów, plus prawdziwe orzeczenia i obwieszczenia urzędów. Pytania: rodzaj pisma, czy biegnie termin, pilność, dział.
Files
| File | Documents | Source | Labels |
|---|---|---|---|
sad_test, adm_test, ksieg_test |
120 each | generated by Bielik 11B v3 from recipes | by construction, automatically checked |
email_test |
120 | written by Claude (Anthropic) from recipes | by construction, rule-checked, rules from SPEC.md |
sad_dev, adm_dev, ksieg_dev, email_dev |
30 each | as above | as above |
sad_real_test |
89 | real court rulings, SAOS 2024–2026 (already anonymised) | document type from SAOS metadata |
sad_real_fragmenty_test |
31 | SAOS texts that start mid-text, with no header | reported separately (type often undecidable) |
sad_real_dev |
120 | SAOS 2025–2026, disjoint from test | document type from metadata |
adm_real_test |
56 | real public notices from 10 offices (samorzad.gov.pl), de-duplicated by template, personal data replaced with [OSOBA]/[ADRES] |
labelled by Claude following SPEC.md, checked by two blind re-labellings and adjudicated; not human-reviewed |
Each line: id, domain, split, state (document text), questions (typed questions in the TypeSafe Jev systemone format), expected (gold answers), source (where applicable), author, labels and note.
Questions
rodzaj/dzial/kategoria_kosztu: choice from a fixed list.termin: yes/no. Does a deadline for the recipient's action run?pilnosc: score 0–3, from the deadline length counted from the letter date: 0 nothing to do, 1 no deadline or > 14 days, 2 8–14 days, 3 ≤ 7 days or immediately. E-mails have their own scale: blocked customer = 2; damage, threat of court or "today" = 3.- E-mail:
rezygnacja(terminates service or account; a single-purchase return does not count),zdenerwowany(upset; a threat of court or media counts).
Every rule and every decision taken while building the set is listed in docs/SPEC.md in the code repository.
Configurations on the Hub: sad, adm, ksieg, email (generated; test and validation = dev), sad_real (test, validation), sad_real_fragmenty, adm_real. Domain codes: sad court, adm administrative, ksieg accounting, email customer e-mail.
from datasets import load_dataset
ds = load_dataset("trenify/jerzyk-bench", "adm_real", split="test")
Personal data
- Real court rulings come from SAOS, where parties are already anonymised. Before publication we also replaced names of judges, prosecutors and court clerks with
[SĘDZIA],[OSOBA]and[PROTOKOLANT](scripts/anonymize_rulings.py). - Real public notices are official documents published by the offices. Names and addresses of private persons were replaced with
[OSOBA]and[ADRES]. Names of offices, their official contact details and parcel numbers were kept. - Generated documents use invented names and companies. PESEL numbers, phone numbers and e-mail domains were masked.
- Check before publication. All 296 real documents were then read in full by two independent automated read-throughs (Claude Opus and Claude Sonnet) looking for remaining personal data; 11 leaks were found and masked (
MANUAL_FIXESinscripts/anonymize_rulings.py). Names of authors of cited legal commentaries were kept, as published literature. This was not a manual human review. - Anonymisation can still miss something. If you find personal data in this dataset, write to contact@trenify.org with the document id (please do not quote it in public discussions), and we will remove it.
- Data protection and copyright requests (for example from a person a document concerns): contact@trenify.org.
Metrics
Accuracy per question, mean over domains, ±1 accuracy and MAE for scores, Brier score for yes/no, ECE (15 bins), and latency. See scripts/evaluate.py in the repository. Do not train on the test split. Use dev for model selection and calibration.
Results
Generated test set (480 documents) — accuracy (%)
| Question | Jerzyk 1.0 (322M) | basal-2.0-mini (1.5B) | Qwen3 8B | Bielik 11B v3 |
|---|---|---|---|---|
| Administrative: urgency | 77.5 | 61.7 | 42.5 | 54.2 |
| Administrative: document_type | 90.0 | 92.5 | 90.8 | 95.0 |
| Administrative: deadline | 82.5 | 79.2 | 84.2 | 83.3 |
| Customer e-mail: department | 93.3 | 88.3 | 89.2 | 88.3 |
| Customer e-mail: urgency | 79.2 | 74.2 | 70.8 | 80.8 |
| Customer e-mail: cancellation | 99.2 | 100.0 | 97.5 | 96.7 |
| Customer e-mail: upset | 91.7 | 90.8 | 77.5 | 85.0 |
| Accounting: cost_category | 97.5 | 95.0 | 85.0 | 75.8 |
| Accounting: urgency | 64.2 | 35.8 | 48.3 | 63.3 |
| Accounting: document_type | 94.2 | 91.7 | 95.8 | 95.8 |
| Accounting: deadline | 85.8 | 95.8 | 94.2 | 77.5 |
| Court: urgency | 80.0 | 42.5 | 38.3 | 54.2 |
| Court: document_type | 84.2 | 96.7 | 94.2 | 92.5 |
| Court: deadline | 93.3 | 85.0 | 83.3 | 82.5 |
| Mean over domains | 86.4 | 80.1 | 77.3 | 79.9 |
Real documents (89 court rulings + 56 administrative notices) — accuracy (%), 95% confidence interval in brackets
| Question | Jerzyk 1.0 (322M) | basal-2.0-mini (1.5B) | Qwen3 8B | Bielik 11B v3 |
|---|---|---|---|---|
| Admin. notices (real): urgency | 58.9 (46–71) | 37.5 (26–51) | 48.2 (36–61) | 32.1 (21–45) |
| Admin. notices (real): document_type | 85.7 (74–93) | 76.8 (64–86) | 83.9 (72–91) | 85.7 (74–93) |
| Admin. notices (real): deadline | 73.2 (60–83) | 76.8 (64–86) | 62.5 (49–74) | 82.1 (70–90) |
| Court rulings (real): document_type | 98.9 (94–100) | 93.3 (86–97) | 100.0 (96–100) | 100.0 (96–100) |
| Mean over domains | 85.8 | 78.5 | 82.4 | 83.3 |
| Jerzyk 1.0 (322M) | basal-2.0-mini (1.5B) | Qwen3 8B | Bielik 11B v3 | |
|---|---|---|---|---|
| ECE, real documents (lower = better) | 0.104 | 0.127 | 0.197 | 0.142 |
| Median latency per document (all models on the same computer) | 0.05 s | 0.28 s | 1.75 s | 3.01 s |
Models compared: Jerzyk 1.0 (calibrated); basal-2.0-mini (MLX 8-bit, native /v1/systemone); Qwen3 8B and Bielik 11B v3.0 Instruct (GGUF Q4_K_M in llama.cpp, zero-shot, answer chosen from option log-probabilities). Mean over domains averages the questions of each domain first, then the domains, so every domain counts equally.
Note. These results were measured on the benchmark text before anonymisation of the real documents (names of judges, officials and private persons replaced with placeholders such as
[SĘDZIA]and[OSOBA]). On the published, anonymised text Jerzyk 1.0 scores 85.5% instead of 85.8% on real documents. The other models will be re-measured on the published text in a later update.
Caveats
- The generated sets use recipes, so their language is cleaner than real mail. Report real and generated results separately.
- The test documents for court, administrative and accounting were written by Bielik 11B, which may favour Bielik slightly.
- Urgency and deadline conventions are those of
SPEC.md. A model that has not seen them is evaluated zero-shot.
About
Jerzyk and jerzyk-bench are published by Fundacja Trenify (Trenify Foundation), a Polish non-profit foundation. Issues and pull requests are welcome on GitHub. Contact: contact@trenify.org (also for security, personal-data and copyright reports).
Citation
@misc{jerzykbench2026,
title = {jerzyk-bench: a Polish benchmark for decision models on official correspondence},
author = {{Fundacja Trenify}},
year = {2026},
howpublished = {\url{https://huggingface.co/datasets/trenify/jerzyk-bench}}
}
License
Apache 2.0. Court rulings (SAOS) and public notices are official documents (art. 4 of the Polish Copyright Act). Generated documents use invented names and data.