Dataset Card for PARHAF-response_to_treatment-annotated

Reporting Issues & Contributing

If you encounter any errors or inconsistencies in this dataset, please report them in the discussion section of the "Community" tab on Hugging Face.

For more substantial contributions or collaboration opportunities, feel free to contact us directly.

Dataset Summary

PARHAF-response_to_treatment-annotated is a subpart of the PARHAF corpus, an open French corpus of human-authored clinical reports of fictional patients.

It was created to support the development and evaluation of clinical NLP systems for the extraction and classification of treatment response levels from oncology consultation reports using RECIST-based categories..

This dataset contains training data only. The test set will remain under embargo to enable future evaluations under controlled conditions, limiting the risk of LLM contamination through prior data exposure. Please contact us for access to the test data.

This training dataset is divided into a train split (80%) and a dev split (20%) to facilitate experimental design and reproducibility across teams. Teams are free to use the full training set or define a different split configuration.

Each patient record was:

• written by a senior medical resident
• reviewed by another senior medical resident, from the same specialty
• annotated by a specialist of the use case
• curated by another specialist of the use case

Data statistics

DATASET SUMMARY

Indicator	Value
Complete Dataset
Number of JSON files	108
Total annotations	211
Average document length	2573 characters
80% Threshold (annotations)	168

Complete dataset distribution by type

Type	Annotations	% of total
DocumentMetadata	108	51.18%
Span	103	48.82%

Complete dataset distribution by populated field

Type.Field	Occurrences	% of total annot.
DocumentMetadata.Nomenclature	108	51.18%
Span.Justification	103	48.82%

Train / Dev Split Results

Indicator	TRAIN	DEV
Number of files	85	23
Number of annotations	168	43
Percentage of dataset	79.62%	20.38%
Avg. document length (chars)	2589	2515

Train / Dev distribution by type

Type	TRAIN	DEV	% train of type
DocumentMetadata	85	23	78.70%
Span	83	20	80.58%

Train / Dev distribution by populated field

Type.Field	TRAIN	DEV	% train of field
DocumentMetadata.Nomenclature	85	23	78.70%
Span.Justification	83	20	80.58%

Train / Dev distribution by value

Type.Field.Value	TRAIN	DEV	% train
Span.Justification.Justification	83	20	80.58%
DocumentMetadata.Nomenclature.ReponsePartielle	33	6	84.62%
DocumentMetadata.Nomenclature.MaladieProgressive	17	3	85.00%
DocumentMetadata.Nomenclature.MaladieStable	15	5	75.00%
DocumentMetadata.Nomenclature.NonApplicable	9	6	60.00%
DocumentMetadata.Nomenclature.ReponseComplete	8	3	72.73%
DocumentMetadata.Nomenclature.NonDetermine	3	0	100.00%

Data Origin

The clinical reports are extracted from the PARHAF corpus. Please refer to PARHAF documentation for more information about this corpus.

Languages

• fr_FR

Dataset Structure

We distribute both a Hugging Face dataset and a standalone version of the corpus. The standalone dataset consists of a JSON file per patient report, in UIMA CAS JSON format. This format constitutes the canonical version of the corpus. The Hugging Face dataset (Parquet/Arrow) is a derived representation generated automatically from the JSON files.

Both formats therefore contain identical information and differ only in storage layout.

One dataset instance corresponds to one report.

Hugging Face dataset

This snippet shows how to extract and iterate over medical report information per patient using the datasets library.

import pandas as pd
from datasets import load_dataset

dfs = {cfg: load_dataset("HealthDataHub/PARHAF-response_to_treatment-annotated", cfg, split="train").to_pandas()
       for cfg in ["document_metadata", "spans"]}

for patient_raw in dfs["document_metadata"].itertuples():
    report_id = patient_raw.report
    text = patient_raw.full_text
    annot_type = patient_raw.annotation_type
    nomenclature = patient_raw.attribute_Nomenclature
    report_spans = dfs["spans"][dfs["spans"]["report"] == report_id]
    ...

Data Fields

Path	Type	Description	Possible values
document_metadata
report	string	Identifiant unique du rapport
full_text	string	Texte intégral du rapport
spans
report	string	Identifiant du rapport
span_id	integer	Identifiant de l'annotation
span_type	string	Type de l'entité annotée	Span
begin	integer	Offset de début
end	integer	Offset de fin
span_text	string	Texte de l'entité
attribute_Justification	string	Justification	Justification

Data Splits

Only the training set is released here. The remaining portion of the corpus will be temporarily embargoed to enable future evaluations under controlled conditions, thereby limiting the risk of large language model contamination through prior exposure to the data. You can evaluate your system on the test set through the CodaBench platform.

Annotation Guidelines

You can find the detailed annotation protocol here: annotation_guidelines.pdf

Licensing Information

This dataset is released under licenses:

• CC BY 4.0
• Etalab 2.0

Citation Information

[More Information Needed]