Update README.md

README.md

@@ -52,9 +52,9 @@ task_ids:
 
 ### Dataset Summary
 
-This dataset can be used to build extractive-QA and Language Models. It is an aggregation and balancing of 2 previous datasets: VilaQUAD and ViquiQUAD, which were described in [The Catalan Language CLUB](https://arxiv.org/abs/2112.01894).
+This dataset can be used to build extractive-QA and Language Models. It is an aggregation and balancing of 2 previous datasets: [VilaQuAD](https://huggingface.co/datasets/projecte-aina/vilaquad) and [ViquiQuAD](https://huggingface.co/datasets/projecte-aina/viquiquad), which were described in [The Catalan Language CLUB](https://arxiv.org/abs/2112.01894).
 
-Splits have been balanced by kind of question, and unlike other datasets like SQuAD, it only contains, per record, one question and one answer for each context, although the contexts can repeat multiple times.
+Splits have been balanced by kind of question, and unlike other datasets like [SQuAD](http://arxiv.org/abs/1606.05250), it only contains, per record, one question and one answer for each context, although the contexts can repeat multiple times.
 
 ### Supported Tasks and Leaderboards
 Extractive-QA, Language Model.
@@ -88,7 +88,7 @@ The dataset is in Catalan (`ca-CA`).
 ```
 
 ### Data Fields
-Follows [Rajpurkar, Pranav et al., 2016](http://arxiv.org/abs/1606.05250) for SQUAD v1 datasets:
+Follows [Rajpurkar, Pranav et al., 2016](http://arxiv.org/abs/1606.05250) for SQuAD v1 datasets:
 
 - `id` (str): Unique ID assigned to the question.
 - `title` (str): Title of the article.
@@ -120,7 +120,7 @@ Volunteers from [Catalan Wikipedia](ca.wikipedia.org) and professional journalis
 
 ### Annotations
 #### Annotation process
-We commissioned the creation of 1 to 5 questions for each context, following an adaptation of the guidelines from SQUAD 1.0 ([Rajpurkar, Pranav et al. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text.” EMNLP (2016)](http://arxiv.org/abs/1606.05250)).
+We commissioned the creation of 1 to 5 questions for each context, following an adaptation of the guidelines from SQuAD 1.0 ([Rajpurkar, Pranav et al. “SQuAD: 100, 000+ Questions for Machine Comprehension of Text.” EMNLP (2016)](http://arxiv.org/abs/1606.05250)).
 
 #### Who are the annotators?
 Annotation was commissioned by a specialized company that hired a team of native language speakers.