Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
query_id: string
query: string
specialty: string
complexity: string
title: string
publisher: string
source_type: string
country: string
doc_id: string
language: string
to
{'doc_id': Value('string'), 'title': Value('string'), 'source_type': Value('string'), 'language': Value('string'), 'country': Value('string'), 'publisher': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
^^^^^^^^^
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
query_id: string
query: string
specialty: string
complexity: string
title: string
publisher: string
source_type: string
country: string
doc_id: string
language: string
to
{'doc_id': Value('string'), 'title': Value('string'), 'source_type': Value('string'), 'language': Value('string'), 'country': Value('string'), 'publisher': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
MIRAGE-PT: Portuguese Clinical RAG Benchmark
The first public benchmark for evaluating retrieval-augmented generation systems on Portuguese clinical text.
Overview
MIRAGE-PT provides 500 clinical queries across 6 medical specialties with human relevance judgments, enabling systematic evaluation of retrieval strategies for Brazilian clinical decision support systems.
| Stat | Value |
|---|---|
| Queries | 500 |
| Specialties | 6 |
| Relevance judgments | 1,487 |
| Corpus documents | 25 |
| Language | Brazilian Portuguese |
| Annotation | LLM-as-judge (κ=0.954) |
Specialties
| Specialty | Simple | Complex | Total |
|---|---|---|---|
| Pharmacology | 97 | — | 97 |
| Clinical Decision | 40 | 60 | 100 |
| Emergency | 57 | 23 | 80 |
| Pricing/Coverage | 75 | — | 75 |
| Pediatrics | 48 | 22 | 70 |
| Clinical Protocols | 45 | 25 | 70 |
Files
| File | Description |
|---|---|
queries.jsonl |
500 clinical queries with specialty and complexity labels |
corpus.jsonl |
25 Brazilian clinical guideline documents (MS, CONITEC, ANVISA) |
qrels.txt |
TREC-format relevance judgments (1,487 query-document pairs) |
evaluate.py |
Evaluation script (Recall@k, P@5, NDCG@5) |
Quick Start
from datasets import load_dataset
ds = load_dataset("igor-eduardo-research/mirage-pt")
Evaluation
python3 evaluate.py --results your_results.jsonl
Results format (your_results.jsonl):
{"query_id": "Q0001", "doc_ids": ["DOC0003", "DOC0007", "DOC0001"]}
Baselines
| System | Recall@5 | P@5 | NDCG@5 |
|---|---|---|---|
| BM25-only | 99.0% | — | — |
| Dense-only (t=0.20) | 77.8% | — | — |
| Dense-only (t=0.60) | 20.2% | — | — |
| Hybrid+RRF (no authority) | 95.6% | — | 0.354 |
| Hybrid+RRF+Authority | 96.6% | 29.8% | 0.354 |
Submit your system's results by opening an issue with your results.jsonl.
Corpus Sources
All documents are publicly available Brazilian clinical references:
- Ministério da Saúde (MS) — Clinical protocols, Cadernos de Atenção Básica
- CONITEC — PCDTs (Protocolos Clínicos e Diretrizes Terapêuticas)
- ANVISA / CMED — Regulatory and pricing references
- DATASUS — CID-10 coding reference
- RENAME 2024 — National essential medicines list
Citation
@misc{eduardo2026miragept,
title = {BM25 and Dense Retrieval Are Complementary for Portuguese Clinical Text:
An Empirical Study of Hybrid RAG Across 500 Clinical Queries},
author = {Eduardo, Igor},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.19686739},
url = {https://doi.org/10.5281/zenodo.19686739}
}
License
CC BY 4.0 — Igor Eduardo, 2026.
- Downloads last month
- 43