Update README.md

README.md

@@ -43,3 +43,91 @@ configs:
   - split: test
     path: data/test-*
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+# Dataset Card for BioRel
+
+## Dataset Description
+
+- **Repository:** https://drive.google.com/drive/folders/1vw2zIxdSoqT2QALDbRVG6loLsgi2doBG
+- **Paper:** [BioRel: towards large-scale biomedical relation extraction](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03889-5)
+
+#### Dataset Summary
+
+<!-- Provide a quick summary of the dataset. -->
+**BioRel Dataset Summary:**
+
+BioRel is a comprehensive dataset designed for biomedical relation extraction, leveraging the vast amount of electronic biomedical literature available. 
+Developed using the Unified Medical Language System (UMLS) as a knowledge base and Medline articles as a corpus, BioRel utilizes Metamap for entity identification and linking, and employs distant supervision for relation labeling. 
+The training set comprises 534,406 sentences, the validation set includes 218,669 sentences, and the testing set contains 114,515 sentences. 
+This dataset supports both deep learning and statistical machine learning methods, providing a robust resource for training and evaluating biomedical relation extraction models.
+The original dataset is available here: https://drive.google.com/drive/folders/1vw2zIxdSoqT2QALDbRVG6loLsgi2doBG
+
+We converted the dataset to the OpenNRE format using the following script: https://github.com/GDAMining/gda-extraction/blob/main/convert2opennre/convert_biorel2opennre.py
+
+### Languages
+
+The language in the dataset is English.
+
+
+## Dataset Structure
+
+<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+
+### Dataset Instances
+
+An example of 'train' looks as follows:
+```json
+{
+  "text": "algal polysaccharide obtained from carrageenin protects 80 to 100 percent of chicken embryos against fatal infections with the lee strain of influenza virus .",
+  "relation": "NA",
+  "h": {
+    "id": "C0032594",
+    "name": "polysaccharide",
+    "pos": [6, 20]
+  },
+  "t": {
+    "id": "C0007289",
+    "name": "carrageenin",
+    "pos": [35, 46]
+  }
+}
+```
+
+### Data Fields
+
+- `text`: the text of this example, a `string` feature.
+- `h`: head entity
+    - `id`: identifier of the head entity, a `string` feature.
+    - `pos`: character offsets of the head entity, a list of `int32` features.
+    - `name`: head entity text, a `string` feature.
+- `t`: tail entity
+    - `id`: identifier of the tail entity, a `string` feature.
+    - `pos`: character offsets of the tail entity, a list of `int32` features.
+    - `name`: tail entity text, a `string` feature.
+- `relation`: a class label.
+
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+```
+@article{xing2020biorel,
+  title={BioRel: towards large-scale biomedical relation extraction},
+  author={Xing, Rui and Luo, Jie and Song, Tengwei},
+  journal={BMC bioinformatics},
+  volume={21},
+  pages={1--13},
+  year={2020},
+  publisher={Springer}
+}
+```
+
+**APA:**
+
+- Xing, R., Luo, J., & Song, T. (2020). BioRel: towards large-scale biomedical relation extraction. BMC bioinformatics, 21, 1-13.
+
+## Dataset Card Authors
+
+[@phucdev](https://github.com/phucdev)