Update README.md

README.md

@@ -7,9 +7,14 @@ size_categories:
 # WebOrganizer/Corpus-200B
 [[Paper](https://arxiv.org/abs/2502.10341)] [[Website](https://weborganizer.allenai.org)] [[GitHub](https://github.com/CodeCreator/WebOrganizer)]
 
-We pre-process the `1b-1x` pool from DataComps-LM using [RefinedWeb filters](https://github.com/mlfoundations/dclm/blob/main/baselines/baselines_configs/dclm_baseline_refinedweb.yaml) and [BFF deduplication](https://github.com/mlfoundations/dclm/tree/main/dedup/bff).
-The resulting 200B token corpus is available here together with quality scores and domain annotations.
+This dataset is a pre-processed version of the `1b-1x` CommonCrawl pool from DataComps-LM cleaned with
+(1) [RefinedWeb filters](https://github.com/mlfoundations/dclm/blob/main/baselines/baselines_configs/dclm_baseline_refinedweb.yaml) and
+(2) [BFF deduplication](https://github.com/mlfoundations/dclm/tree/main/dedup/bff).
+
+We provide the resulting 200B token corpus annotated with two quality scores, WebOrganizer domains, and k-means scores.
+
 __Download the dataset by cloning the repository with Git LFS instead of HuggingFace's `load_dataset()`.__
+
 The dataset has the following folder structure:
 ```bash
 Corpus-200B/
@@ -17,7 +22,7 @@ Corpus-200B/
         - CC_shard_00000000_processed.jsonl.zst
         - CC_shard_00000001_processed.jsonl.zst
         - ...
-    tokens/  # number of tokens per document
+    tokens/  # number of tokens per document (GPT-NeoX tokenizer)
         - CC_shard_00000000_processed.npy
         - CC_shard_00000001_processed.npy
         - ...
@@ -41,7 +46,10 @@ Corpus-200B/
         - ...
 ```
 We also include statistics about the presence and co-occurence of domains in the `domain_statistics/` folder, computed with the `domain_statistics.py` script.
+
 ## Citation
+
+If you make use of this pre-processed corpus in your work, please cite:
 ```bibtex
 @article{wettig2025organize,
   title={Organize the Web: Constructing Domains Enhances Pre-Training Data Curation},