Update README.md

README.md

@@ -42,4 +42,104 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- biology
+- relation-classification
+pretty_name: TBGA
+size_categories:
+- 100K<n<1M
 ---
+# Dataset Card for TBGA
+
+## Dataset Description
+
+- **Repository:** https://github.com/GDAMining/gda-extraction
+- **Paper:** [TBGA: a large‑scale Gene‑Disease Association dataset for Biomedical RelationExtraction](https://link.springer.com/epdf/10.1186/s12859-022-04646-6?sharing_token=qgaQQs92ZxFpodts5HhcmW_BpE1tBhCbnbw3BuzI2RNBkapcoPX8TYwxqVikGDmcarZHWjFQGawSFYjAFhD3cB50vnZY-JefC9csY__WaxOMsnqCn5_cyZrmWMAyl_T3CruatRTM1QvUt6DbcOiPnb7cks1YDxyHWkekMqdYB1A%3D)
+
+#### Dataset Summary
+
+<!-- Provide a quick summary of the dataset. -->
+TBGA is a comprehensive dataset created for the purpose of Gene-Disease Association (GDA) extraction, generated from over 700,000 publications. 
+It features more than 200,000 instances and 100,000 unique gene-disease pairs. 
+Each instance in the dataset includes the specific sentence from which the GDA was extracted, the extracted GDA itself, and detailed information about the gene-disease pair involved. 
+This dataset was semi-automatically annotated by Marchesin and Silvello using data sourced from the DisGeNET database, which houses one of the most extensive collections of genes and variants associated with human diseases.
+The dataset follows the OpenNRE format and contains the following relations:
+```json
+{"NA": 0, "therapeutic": 1, "biomarker": 2, "genomic_alterations": 3}
+```
+
+### 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": "A monocyte chemoattractant protein-1 gene polymorphism is associated with occult ischemia in a high-risk asymptomatic population.",
+  "relation": "NA",
+  "h": {
+    "id": 6347,
+    "name": "CCL2",
+    "pos": [2, 34]
+  },
+  "t": {
+    "id": "C0231221",
+    "name": "Asymptomatic",
+    "pos": [105, 12]
+  }
+}
+```
+
+
+### 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{marchesin-silvello-2022,
+  title = "TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation Extraction",
+  author = "S. Marchesin and G. Silvello",
+  journal = "BMC Bioinformatics",
+  year = "2022",
+  url = "https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04646-6",
+  doi = "10.1186/s12859-022-04646-6",
+  volume = "23",
+  number = "1",
+  pages = "111"
+}
+```
+
+**APA:**
+
+- Marchesin, S., & Silvello, G. (2022). TBGA: A large-scale Gene-Disease Association dataset for Biomedical Relation Extraction. BMC Bioinformatics, 23(1), 111. https://doi.org/10.1186/s12859-022-04646-6
+
+## Dataset Card Authors
+
+[@phucdev](https://github.com/phucdev)