Update README.md

README.md

@@ -56,32 +56,37 @@ dataset_info:
   download_size: 47727501
   dataset_size: 286790625
 splits:
-- name: test
+- name: train
 configs:
 - config_name: default
   data_files:
-  - split: test
-    path: data/test-*
+  - split: train
+    path: data/train-*
 ---
 
 # Dataset Card for sst2_cognitive-bias
-<!-- Provide a quick summary of the dataset. -->
 
 This dataset is a modification of the original [SST-2](https://huggingface.co/datasets/stanfordnlp/sst2) dataset for LLM cognitive bias evaluation.
 
-- **Language(s):** English (`en`)
+## Language(s)
 
-## Dataset Structure
+- English (`en`)
+
+## Dataset Summary
+
+The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language. 
+The corpus is based on the dataset introduced by Pang and Lee (2005) and consists of 11,855 single sentences extracted from movie reviews. It was parsed with the Stanford parser and includes a total of 215,154 unique phrases from those parse trees, each annotated by 3 human judges.
 
-- **idx**: original id in SST-2 dataset in the format `\<partition\>_\<id\>`.
-- **sentence**: test sentence.
-- **few_shot_string**: 4-shot string with examples from the original training split.
-- **few_shot_hard_string**: 5-shot string with the same examples as in `few_shot_string`, but with a neutral example inserted between the first and the last 2.
+## Dataset Structure
 
 The modifications carried out in the dataset are thought to evaluate cognitive biases in a few-shot setting and with different task complexities. 
 We make use of 25k instances from the original dataset, while the remaining ones serve as few-shot examples.
-Each instance is prompted with all possible unbalanced 4-shot distributions (`few_shot_string`), i.e. balanced distributions are not considered.
-We also increase task complexity by introducing an additional neutral example between the first and last two examples (`few_shot_hard_string`).
+Each instance is prompted with all possible unbalanced 4-shot distributions.
+We increase task complexity by introducing an additional neutral example between the first and last two examples.
+
+## Supported Tasks and Leaderboards
+
+- `sentiment-classification`
 
 ## Citation