Add the RadGraph-IT dataset

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README.md

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+---
+pretty_name: RadGraph-IT
+language:
+- it
+task_categories:
+- token-classification
+size_categories:
+- n<1K
+tags:
+- radiology
+- clinical-nlp
+- named-entity-recognition
+- relation-extraction
+- radgraph
+- italian
+configs:
+- config_name: sample
+  data_files:
+  - split: train
+    path: data/radgraph_it_50.jsonl
+---
+
+# RadGraph-IT Dataset
+
+## Dataset summary
+
+RadGraph-IT contains 2,850 Italian radiology reports with entity and relation
+annotations in a DyGIE-compatible JSONL format. The corpus combines 2,300
+reports from [RadGraph-XL](https://aclanthology.org/2024.findings-acl.765/)
+with 550 reports derived from
+[RadGraph 1.0](https://physionet.org/content/radgraph/1.0.0/).
+
+This repository provides a 50-report excerpt of the corpus used for training.
+The complete RadGraph-IT corpus is not currently available for publication.
+The full corpus includes 1,050 chest X-ray reports, 600 chest CT reports, 600
+abdomen/pelvis CT reports, and 600 brain MRI reports.
+
+## Translation and manual review
+
+All 2,850 English reports were localized with the English-to-Italian pipeline
+developed for the thesis *AI-Driven Keyword Extraction and Structuralization
+of Medical Reports* and released in the
+[`EIDOSLAB/radiomicslab-keyword-extraction`](https://github.com/EIDOSLAB/radiomicslab-keyword-extraction)
+repository.
+
+After translation and span remapping, the localized reports and projected
+annotations were manually reviewed. The Italian text, entity boundaries,
+entity labels, and relations were corrected where necessary.
+
+## Annotation schema
+
+Each entity is a contiguous, inclusive token span assigned one of six labels:
+
+- `Anatomy::definitely present`
+- `Anatomy::uncertain`
+- `Anatomy::definitely absent`
+- `Observation::definitely present`
+- `Observation::uncertain`
+- `Observation::definitely absent`
+
+Entities are connected by three directed relation types:
+
+- `located_at`: an Observation and its anatomical site;
+- `suggestive_of`: an Observation and another observation that it suggests;
+- `modify`: two Observations or two Anatomy entities when one qualifies the
+  other.
+
+## Data format
+
+The included [`data/radgraph_it_50.jsonl`](data/radgraph_it_50.jsonl)
+uses the same representation consumed by the training stack. Each line is one
+JSON object with:
+
+- `dataset`: a provenance-aware RadGraph-IT source and modality label, such as
+  `radgraph-it-stanford-chest-x-ray`;
+- `doc_key`: the numeric index from the original source subset; the pair
+  `(dataset, doc_key)` uniquely identifies and traces each report;
+- `sentences`: a list containing the tokenized report;
+- `ner`: entity tuples `[start, end, label]`, with inclusive token indices;
+- `relations`: directed relation tuples
+  `[source_start, source_end, target_start, target_end, label]`, with inclusive
+  token indices.
+
+The entire report is represented as one DyGIE "sentence" so relations can
+connect entities anywhere in the report.
+
+## Sample distribution
+
+The 50-report excerpt is distributed across the four imaging modalities as follows:
+
+| Modality | Sample reports |
+|---|---:|
+| Chest X-ray | 18 |
+| Chest CT | 11 |
+| Abdomen/pelvis CT | 11 |
+| Brain MRI | 10 |
+| **Total** | **50** |