Update README.md

README.md

@@ -125,7 +125,7 @@ The synthetic data is pulled from [AskNews API](https://docs.asknews.app), which
 
 The [AskNews API](https://docs.asknews.app) uses open-web news articles to generate synthetic data (news article summaries) with Llama2/3. This dataset was pulled from the API by querying 4 hour buckets of articles between February 20 and March 31, 2024. These buckets were then processed with the following steps:
 
-4. Cluster embeddings according to topic, for each 4 hour bucket of articles throughout the duration of February 20-March 30 2024.
+4. Cluster embeddings according to topic, for 29 4-hour buckets of articles evenly dispersed throughout the duration of February 20-March 30 2024.
 5. Pull samples from clusters, distributing evenly across country of origin.
 6. Extract entities from each summary using Llama3.
 
@@ -158,7 +158,7 @@ This dataset does not contain any information that is not publicly available on
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-Although the goal of the dataset is to reduce bias, and improve diversity, it is still biased to western languages and countries. This limitation originates from the abilities of Llama2 for the translation and summary generations. Further, any bias originating in Llama2 training data will also be present in this dataset, since Llama2 was used to summarize the open-web articles. Further, any biases present in Llama3 will be present in the present dataaset since Llama3 was used to extract entities from the summaries.
+Although the goal of the dataset is to reduce bias, and improve diversity, it is still biased to western languages and countries. This limitation originates from the abilities of Llama2 for the translation and summary generations. Further, any bias originating in Llama2 training data will also be present in this dataset, since Llama2 was used to summarize the open-web articles. Further, any biases present in Llama3 will be present in the present dataset since Llama3 was used to extract entities from the summaries.
 
 ![countries distribution](figures/topics_fig_connected.png)