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README.md

@@ -1,3 +1,14 @@
+---
+license: mit
+tags:
+- mathematics
+- education
+- reasoning
+- trap-questions
+- math-problems
+library_name: datasets
+---
+
 # MathTrap300
 
 A benchmark dataset of 300 insolvable, ill-posed mathematical problems designed to evaluate large language models' ability to recognize mathematical insolvability and fundamental contradictions.
@@ -23,7 +34,7 @@ from datasets import load_dataset
 dataset = load_dataset("GYASBGFUHAADSGADF/mathtrap300")
 
 # Access the data
-for example in dataset['batch1']:
+for example in dataset['train']:
     print(f"Original: {example['original']}")
     print(f"Trap: {example['trap']}")
     print(f"Annotation: {example['annotation']}")
@@ -50,6 +61,15 @@ Our evaluation of recent advanced LLMs on MathTrap300 reveals:
   - Condition Neglect: Models ignore critical mathematical constraints
 - **Forced Solutions**: Even when models recognize insolvability, they still attempt to force a solution
 
+## Dataset Statistics
+
+- **Total Problems**: 300 (currently 151 uploaded)
+- **Difficulty Levels**: 1.0 - 5.0
+- **Trap Types**: Contradiction, Missing Conditions, and others
+- **Sources**: MATH dataset, Original creation
+- **Validation**: Rigorously verified by PhD-level mathematical experts
+- **Split**: Mix of train/test examples
+
 ## Citation
 
 If you use this dataset in your research, please cite our paper:
@@ -66,4 +86,4 @@ If you use this dataset in your research, please cite our paper:
 
 ## License
 
-This dataset is released under the MIT License.
+This dataset is released under the MIT License.