Update README.md

README.md

@@ -45,19 +45,18 @@ size_categories:
 
 ## Dataset Description
 
-- **Website:** 
 - **Point of Contact:** [email protected]
 
 
 ### Dataset Summary
 
-The CA-PT Parallel Corpus is a Catalan-Portuguese dataset of **9.892.953** parallel sentences. The dataset was created to support Catalan NLP tasks, e.g., 
+The CA-PT Parallel Corpus is a Catalan-Portuguese dataset of **9.892.953** parallel sentences. The dataset was created to support Catalan in NLP tasks, specifically 
 Machine Translation.
 
 
 ### Supported Tasks and Leaderboards
 
-The dataset can be used to train a model for Bilingual Machine Translation between Portugues and Catalan in any direction, 
+The dataset can be used to train models for Bilingual Machine Translation between Portuguese and Catalan in any direction, 
 as well as Multilingual Machine Translation models.
 
 ### Languages
@@ -68,7 +67,7 @@ The sentences included in the dataset are in Catalan (CA) and Portuguese (PT).
 
 ### Data Instances
 
-Two separated txt files are provided with the sentences sorted in the same order:
+Two separate txt files are provided with the sentences sorted in the same order:
 
 - ca-pt_2023_09_01_full.ca: contains 9.892.953 Catalan sentences.
 
@@ -93,7 +92,7 @@ This dataset was created to contribute to the development of Machine Translation
 
 #### Initial Data Collection and Normalization
 
-The dataset is a combination of the following authentic datasets:
+The dataset is a combination of the following original datasets:
 
 | Dataset       | Sentences |
 |:-------|-------:|
@@ -121,9 +120,9 @@ The filtered datasets are then concatenated to form a final corpus of **9.892.95
 
 #### Who are the source language producers?
 
-[Opus](https://opus.nlpl.eu/). 
+[Opus](https://opus.nlpl.eu/) 
 
-[SoftCatalà](https://github.com/Softcatala/Europarl-catalan).
+[SoftCatalà](https://github.com/Softcatala/Europarl-catalan)
 
 ### Annotations
 
@@ -147,7 +146,8 @@ We hope this dataset contributes to the development of Machine Translation betwe
 
 ### Discussion of Biases
 
-[N/A]
+This dataset may contain inherent biases that could impact the fairness and accuracy of models trained on it. 
+Users are encouraged to consider potential biases during model development to promote fair and unbiased outcomes.
 
 ### Other Known Limitations