Update README.md

README.md

@@ -37,3 +37,140 @@ configs:
   - split: test2
     path: data/test2-*
 ---
+
+# SIMORD
+
+HuggingFace re-upload of the [SIMORD dataset](https://huggingface.co/datasets/microsoft/SIMORD), **a medical order extraction benchmark based on doctor-patient conversations**, with corrections to data splits and all text transcripts now included by default. If used, please cite the original authors using the citation below.
+
+
+## Dataset Details
+
+### Dataset Sources
+
+- **HuggingFace:** https://huggingface.co/datasets/microsoft/SIMORD
+- **Paper:** https://arxiv.org/pdf/2507.05517
+
+
+### Dataset Description
+
+The dataset contains three splits (with their corresponding original SIMORD files):
+
+1) `train` (from `train.json`): examples for in-context learning or fine-tuning.
+2) `test1` (from `dev.json`): test set used for the EMNLP 2025 industry track paper.
+3) `test2` (from `test.json`): test set for MEDIQA-OE shared task of ClinicalNLP 2025.
+
+With the following distribution
+
+| Split | Original | New | Change |
+| :--- | :---: | :---: | :---: |
+| `train` | 63 | 81 | +18 |
+| `test1` | 100 | 90 | -10 |
+| `test2` | 100 | 92 | -8 |
+| **TOTAL** | **263** | **263** | **-** |
+
+Note: Both the original SIMORD dataset and this upload use the split name `test1` instead of dev/validation (even though the file is `dev.json`) and `test2` instead of test (even though the file is `test.json`), since both were used as test sets.
+
+
+### Dataset Changes
+
+The SIMORD dataset is derived from both [ACI-Bench](https://github.com/wyim/aci-bench) and [PriMock57](https://github.com/babylonhealth/primock57).
+
+While PriMock57 doesn't contain any explicit data splits, ACI-Bench contains five splits: `train`, `valid`, `test1`, `test2`, and `test3`. As discussed in an [open HF issue](https://huggingface.co/datasets/microsoft/SIMORD/discussions/2), these splits were not respected when being merged into SIMORD.
+
+For example, SIMORD's `test.json` contains an ACI-Bench train sample:
+
+`
+"id": "acibench_D2N036_aci_train"
+`
+
+The official SIMORD HF upload contains three data files that are mapped to the following splits
+
+| SIMORD File | Mapped Split | Total | Train | Valid/Dev | Test1 | Test2 | Test3 | PriMock57 |
+|:---|:---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
+| [train.json](https://huggingface.co/datasets/microsoft/SIMORD/blob/main/data/train.json) | `train` | 63 | 15 | 8 | 8 | 10 | 8 | 14 |
+| [dev.json](https://huggingface.co/datasets/microsoft/SIMORD/blob/main/data/dev.json) | `test1` | 100 | 27 | 3 | 20 | 14 | 13 | 23 |
+| [test.json](https://huggingface.co/datasets/microsoft/SIMORD/blob/main/data/test.json) | `test2` | 100 | 25 | 9 | 11 | 16 | 19 | 20 |
+
+
+
+This updated version of SIMORD reallocates samples using the following logic:
+
+- **New `train`** = old train (train+PriMock57 samples) + old test1 (train samples) + old test2 (train samples)
+- **New `test1`** = old test1 (non-train samples) + half of old train (non-train, non-PriMock57 samples)
+- **New `test2`** = old test2 (non-train samples) + half of old train (non-train, non-PriMock57 samples)
+
+In other words:
+- Samples with `_train` suffix are moved to `train`, regardless of which original file they came from
+- PriMock57 samples stay in their original splits, since PriMock57 has no explicit data splits
+- Non-train samples in the original `test1` and `test2` splits stay where they are
+- Non-train, non-PriMock57 samples that were misplaced in the original `train` split are evenly distributed between `test1` and `test2`
+
+After reallocation, the new splits contain the following counts:
+
+| New Split | Total | Train | Valid/Dev | Test1 | Test2 | Test3 | PriMock57 |
+|:---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
+| `train` | 81 | 67 | 0 | 0 | 0 | 0 | 14 |
+| `test1` | 90 | 0 | 7 | 24 | 19 | 17 | 23 |
+| `test2` | 92 | 0 | 13 | 15 | 21 | 23 | 20 |
+
+
+### Direct Use
+
+```python
+import json
+from datasets import load_dataset
+
+
+if __name__ == "__main__":
+    # load all data
+    dataset = load_dataset("mkieffer/SIMORD")
+
+    # load only train split
+    dataset_train = load_dataset("mkieffer/SIMORD", split="train")
+
+    # load only test1 split
+    dataset_test1 = load_dataset("mkieffer/SIMORD", split="test1")
+
+    print("\nfull dataset:\n", dataset)
+    print("\ntrain split:\n", dataset_train)
+    print("\ntest1 split:\n", dataset_test1)
+
+    print("\ntrain sample:\n", json.dumps(dataset_train[0], indent=2))
+    print("\ntest1 sample:\n", json.dumps(dataset_test1[0], indent=2))
+```
+
+
+## Citation 
+
+```bibtex
+@inproceedings{corbeil-etal-2025-empowering,
+    title = "Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications",
+    author = "Corbeil, Jean-Philippe  and
+      Ben Abacha, Asma  and
+      Michalopoulos, George  and
+      Swazinna, Phillip  and
+      Del-Agua, Miguel  and
+      Tremblay, Jerome  and
+      Daniel, Akila Jeeson  and
+      Bader, Cari  and
+      Cho, Kevin  and
+      Krishnan, Pooja  and
+      Bodenstab, Nathan  and
+      Lin, Thomas  and
+      Teng, Wenxuan  and
+      Beaulieu, Francois  and
+      Vozila, Paul",
+    editor = "Potdar, Saloni  and
+      Rojas-Barahona, Lina  and
+      Montella, Sebastien",
+    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track",
+    month = nov,
+    year = "2025",
+    address = "Suzhou (China)",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2025.emnlp-industry.58/",
+    doi = "10.18653/v1/2025.emnlp-industry.58",
+    pages = "859--870",
+    ISBN = "979-8-89176-333-3"
+}
+```