Update README.md

README.md

@@ -24,3 +24,30 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+## dataset summary
+NER-News-BIDataset is a dataset for named entity recognition (NER) in news articles, publicly released by the National Institute of Korean Language in 2023.   
+The dataset is labeled with named entities specifically for news data.   
+It consists of a total of 150,142 sentences, and entities are categorized into 150 labels for recognition.  
+
+## Languages
+korean  
+
+## Data Structure
+DatasetDict({
+    train: Dataset({
+        features: ['input_ids', 'attention_mask', 'labels'],
+        num_rows: 120113
+    })
+    test: Dataset({
+        features: ['input_ids', 'attention_mask', 'labels'],
+        num_rows: 30029
+    })
+})  
+
+### Data Instances
+The dataset is provided in text format with train/test sets.   
+Each instance represents a news article, and if there is an entity in the sentence, it is appropriately tagged with the corresponding label.   
+In cases where a single entity is separated into multiple tokens, the first token is labeled as "B-entity" and the subsequent tokens are labeled as "I-entity" until the end.  
+
+### Data Fields