Update README.md

README.md

@@ -13,10 +13,10 @@ LePaRD is a massive collection of U.S. federal judicial citations to precedent i
 The distribution of passage citation frequency is long tailed, a small number of passages appear thousands of times in the data while many are cited just once of twice. As a result, the passage retrieval task becomes harder as we consider more data. 
 
 We provide four versions of LePaRD:
-* top_10000_data.csv.gz: Contains the data corresponding to the 10,000 most cited passages
-* top_20000_data.csv.gz: Contains the data corresponding to the 20,000 most cited passages
-* top_50000_data.csv.gz: Contains the data corresponding to the 50,000 most cited passages
-* all_data.csv.gz: Contains data associated with all passages.
+* [top_10000_data.csv.gz](https://huggingface.co/datasets/rmahari/LePaRD/blob/main/top_10000_data.csv.gz): Contains the data corresponding to the 10,000 most cited passages
+* [top_20000_data.csv.gz](https://huggingface.co/datasets/rmahari/LePaRD/blob/main/top_20000_data.csv.gz): Contains the data corresponding to the 20,000 most cited passages
+* [top_50000_data.csv.gz](https://huggingface.co/datasets/rmahari/LePaRD/blob/main/top_50000_data.csv.gz): Contains the data corresponding to the 50,000 most cited passages
+* [all_data.csv.gz](https://huggingface.co/datasets/rmahari/LePaRD/blob/main/all_data.csv.gz): Contains data associated with all passages.
 
 Each row of LePaRD contains the following features:
 * passage_id: A unique identifier for each passage
@@ -25,7 +25,7 @@ Each row of LePaRD contains the following features:
 * court: The court from which the passage originated
 * date: The date when the opinion from which the passage originated was published
 
-Passage_ids are mapped to the passage text in passage_dict.json. 
+Passage_ids are mapped to the passage text in [passage_dict.json](https://huggingface.co/datasets/rmahari/LePaRD/blob/main/passage_dict.json).
 Note that multiple slightly different quotes can map to the same passage as judges will sometimes cite different parts of the same sentence.
 
 In the vocabulary of information retrieval, the destination_context can be seen as a query, and the predicted passage_id (or the actual text of a passage in passage_dict.json) can be seen as the targets.