Update README.md

README.md

@@ -104,8 +104,8 @@ configs:
 EA-MT (Entity-Aware Machine Translation) is a multilingual benchmark for evaluating the capabilities of Large Language Models (LLMs) and Machine Translation (MT) models in translating simple sentences with potentially challenging entity mentions, e.g., entities for which a word-for-word translation may not be accurate.
 
 Here is an example of a simple sentence with a challenging entity mention:
-* English: "What is the plot of **The Catcher in the Rye**?"
-* Italian:
+* *English*: "What is the plot of **The Catcher in the Rye**?"
+* *Italian*:
   * Word-for-word translation (incorrect): "Qual è la trama del **Cacciatore nella segale**?"
   * Correct translation: "Qual è la trama de **Il giovane Holden**?"
 
@@ -131,7 +131,7 @@ The dataset is available in the following languages pairs:
 - `en-tr`: English - Turkish
 - `en-zh`: English - Chinese (Traditional)
 
-## How To Use This Benchmark in Hugging Face Datasets
+## How To Use
 
 You can use this benchmark in Hugging Face Datasets by specifying the language pair you want to use. For example, to load the English-Italian dataset, you can use the following configuration: