Update README.md

README.md

@@ -807,3 +807,30 @@ dataset_info:
   download_size: 176268
   dataset_size: 813863
 ---
+
+**Text2DistBench** is a benchmark for evaluating whether large language models can infer distributional knowledge from natural language evidence.
+Given metadata and a set of user comments about an entity (e.g., a movie or song), models must estimate statistics such as:
+stance distribution, topic distribution, and most/second-most frequent labels.
+The dataset is organized into two types of configurations.
+
+**Posterior configurations** include both metadata and user comments as evidence.  
+These configurations differ by sample size (50 or 100 comments) and task type:
+`posterior_sampled_50_estimation`, 
+`posterior_sampled_50_most_freq`,  
+`posterior_sampled_50_second_freq`,  
+`posterior_sampled_100_estimation`, 
+`posterior_sampled_100_most_freq`, 
+`posterior_sampled_100_second_freq`  
+
+**Prior configurations** contain only metadata without comments: `prior_estimation`, `prior_most_freq`, `prior_second_freq`  
+
+---
+
+## Load the Dataset
+
+Example:
+```bash
+from datasets import load_dataset
+ds = load_dataset("frett/Text2DistBench", "posterior_sampled_50_estimation", split="test")
+ds = load_dataset("frett/Text2DistBench", "prior_most_freq", split="test")
+```