Update README.md

README.md

@@ -1,3 +1,40 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- summarization
+language:
+- en
+tags:
+- biomedical
+- health
+- NLP
+- summarization
+- LLM
+- factuality
+size_categories:
+- 1K<n<10K
+---
+
+PlainFact is a high-quality human-annotated dataset with fine-grained explanation (i.e., added information) annotations designed for Plain Language Summarization tasks, along with [PlainQAFact](https://github.com/zhiwenyou103/PlainQAFact) factuality evaluation framework. It is collected from the [Cochrane database](https://www.cochranelibrary.com/) sampled from CELLS dataset ([Guo et al., 2024](https://doi.org/10.1016/j.jbi.2023.104580)). 
+
+We also provided a summary-level version [PlainFact-summary](https://huggingface.co/datasets/uzw/PlainFact-summary) that aggregrated all the sentences as complete summaries. In total, we have 200 plain language summary-abstract pairs.
+
+Currently, we only released the annotation for **Explanation** sentences. We will release the full version of PlainFact soon (including Category and Relation information). Stay tuned!
+
+Here are explanations for the headings:
+- **Target_Sentence**: The plain language sentence/summary.
+- **Original_Abstract**: The scientific abstract corresponding to each sentence/summary.
+- **External**: Whether the sentence includes information does not explicitly present in the scientific abstract. (yes: explanation, no: simplification)
+
+You can load our dataset as follows:
+```python
+from datasets import load_dataset
+plainfact = load_dataset("uzw/PlainFact")
+```
+
+For detailed information regarding the dataset or factuality evaluation framework, please refer to our [Github repo](https://github.com/zhiwenyou103/PlainQAFact) and paper.
+
+Citation
+If you use data from PlainFact or PlainFact-summary, please cite with the following BibTex entry:
+```
+```