Update README

README.md

@@ -1,31 +1,81 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: task_type
-    dtype: string
-  - name: prompt_0shot
-    dtype: string
-  - name: prompt_5shot
-    dtype: string
-  - name: golden_plan
-    dtype: string
-  - name: num_cities
-    dtype: string
-  - name: cities
-    dtype: string
-  - name: durations
-    dtype: string
-  splits:
-  - name: test
-    num_bytes: 34308000
-    num_examples: 3600
-  download_size: 4847966
-  dataset_size: 34308000
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
+license: apache-2.0
+tags:
+- planning
+- natural-language
+- trip-planning
+- meeting-scheduling
+- llm-evaluation
+language:
+- en
+size_categories:
+- 1K<n<10K
 ---
+
+# naturalplan-benchmark
+
+Natural Plan: Benchmarking LLMs on Natural Language Planning (Trip, Meeting, Calendar)
+
+## Dataset Description
+
+This dataset is a standardized version of the original benchmark, prepared for easy evaluation of LLMs on planning tasks.
+
+### Splits
+
+- **test**: 3,600 samples
+
+
+### Features
+
+```python
+{
+  "id": "Value(dtype='string', id=None)",
+  "task_type": "Value(dtype='string', id=None)",
+  "prompt_0shot": "Value(dtype='string', id=None)",
+  "prompt_5shot": "Value(dtype='string', id=None)",
+  "golden_plan": "Value(dtype='string', id=None)",
+  "num_cities": "Value(dtype='string', id=None)",
+  "cities": "Value(dtype='string', id=None)",
+  "durations": "Value(dtype='string', id=None)"
+}
+```
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("tuandunghcmut/naturalplan-benchmark")
+
+# Access splits
+train_data = dataset["train"]  # if available
+test_data = dataset["test"]
+
+# Example
+print(test_data[0])
+```
+
+## Citation
+
+If you use this dataset, please cite the original paper:
+
+```bibtex
+@article{zheng2024naturalplanbenchmarkingllms,
+  title={NATURAL PLAN: Benchmarking LLMs on Natural Language Planning},
+  author={Huaixiu Steven Zheng and Swaroop Mishra and Hugh Zhang and Xinyun Chen and Minmin Chen and Azade Nova and Le Hou and Heng-Tze Cheng and Quoc V. Le and Ed H. Chi and Denny Zhou},
+  year={2024},
+  eprint={2406.04520},
+  archivePrefix={arXiv
+}
+```
+
+## Acknowledgments
+
+This dataset is a reformatted version of the original benchmark. 
+All credit goes to the original authors.
+
+---
+
+**Prepared by**: tuandunghcmut
+**Original Source**: See citation above