Update README.md

README.md

@@ -20,7 +20,7 @@ task_ids:
 - extractive-qa
 ---
 
-# VilaQuAD, An extractive QA dataset for catalan, from VilaWeb newswire text
+# VilaQuAD, An extractive QA dataset for Catalan, from VilaWeb newswire text
 
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
@@ -55,7 +55,7 @@ task_ids:
 
 ### Dataset Summary
 
-VilaQuAD, An extractive QA dataset for catalan, from Vilaweb newswire text.
+VilaQuAD, An extractive QA dataset for Catalan, from [VilaWeb](www.vilaweb.cat) newswire text.
 
 This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
 
@@ -92,7 +92,7 @@ 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 VilaWeb article.
@@ -112,7 +112,7 @@ Follows [Rajpurkar, Pranav et al., 2016](http://arxiv.org/abs/1606.05250) for sq
 
 ### Methodology
 
-From a the online edition of the catalan newspaper [VilaWeb](https://www.vilaweb.cat), 2095 articles were randomnly selected. These headlines were also used to create a Textual Entailment dataset. For the extractive QA dataset, creation of between 1 and 5 questions for each news context was commissioned, 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. In total, 6282 pairs of a question and an extracted fragment that contains the answer were created.
+From a the online edition of the Catalan newspaper [VilaWeb](https://www.vilaweb.cat), 2095 articles were randomnly selected. These headlines were also used to create a Textual Entailment dataset. For the extractive QA dataset, creation of between 1 and 5 questions for each news context was commissioned, 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)). In total, 6282 pairs of a question and an extracted fragment that contains the answer were created.
 
 ### Curation Rationale
 
@@ -120,7 +120,7 @@ For compatibility with similar datasets in other languages, we followed as close
 
 ### Source Data
 
-- https://www.vilaweb.cat/
+- [VilaWeb site](www.vilaweb.cat)
 
 #### Initial Data Collection and Normalization
 
@@ -134,7 +134,7 @@ Professional journalists from the Catalan newspaper [VilaWeb](https://www.vilawe
 
 #### Annotation process
 
-We comissioned 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 comissioned 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?