Update README.md

README.md

@@ -118,7 +118,7 @@ Original Paper: https://ceur-ws.org/Vol-2765/paper164.pdf
 This dataset contains a collection of binary-labelled concept pairs (A,B) extracted from textbooks on four domains: **data mining**, **geometry**, **physics** and **precalculus**.
 Then, domain experts were asked to manually annotate if pairs of concepts showed a prerequisite relation or not, therefore the dataset consists of both positive and negative concept pairs.
 
-We obtained the data from the original repository, making only one modification: undersampling the training data. To evaluate generative models in in-context learning, it's essential to have a balanced distribution for sampling examples in a few-shot setting. The undersampling process was carried out randomly, and separately for each domain.
+We obtained the data from the original repository, making only one modification: undersampling the training data, to have a balanced set. To evaluate generative models in in-context learning, it's essential to have a balanced distribution for sampling examples in a few-shot setting. The undersampling process was carried out randomly, and separately for each domain.
 
 ## Example