Error code:   ConfigNamesError
Exception:    KeyError
Message:      'feature'
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 165, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1664, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1621, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1068, in get_module
                  {
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1069, in <dictcomp>
                  config_name: DatasetInfo.from_dict(dataset_info_dict)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 284, in from_dict
                  return cls(**{k: v for k, v in dataset_info_dict.items() if k in field_names})
                File "<string>", line 20, in __init__
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/info.py", line 170, in __post_init__
                  self.features = Features.from_dict(self.features)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1888, in from_dict
                  obj = generate_from_dict(dic)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1468, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1468, in <dictcomp>
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/features/features.py", line 1480, in generate_from_dict
                  feature = obj.pop("feature")
              KeyError: 'feature'

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📚 DeepResearch Wiki Data

A comprehensive collection of Wikipedia articles about recent events (2023-2025), stored in JSON format. This dataset serves as the source material for the CriticSearch Report Benchmark, containing detailed information about global events, elections, disasters, and other significant occurrences.

🌟 Dataset Overview

Time Period: 2023-2025
Total Articles: 271 articles
Format: JSON files
Source: Wikipedia
Last Updated: 2025-06-06

📊 Content Categories

Elections: 140 articles\n- Other: 81 articles\n- Natural Disasters: 20 articles\n- Sports: 14 articles\n- Social Movements: 8 articles\n- International Conflicts: 8 articles

📅 Year Distribution

2023: 83 articles\n- 2024: 112 articles\n- 2025: 67 articles

📝 Data Format

Each article is stored in a separate JSON file with the following structure:

{
  "title": "2024_United_States_presidential_election",
  "url": "https://en.wikipedia.org/wiki/2024_United_States_presidential_election",
  "content": {
    "sections": [
      {
        "title": "Background",
        "level": 1,
        "content": "Full section content..."
      }
    ],
    "metadata": {
      "last_updated": "2024-03-20",
      "language": "en"
    }
  }
}

🚀 Quick Start

Loading the Dataset

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Looogic/DeepResearch_wiki_data")

# Access the articles
articles = dataset['train']  # All articles are in the train split

print(f"Total articles: {len(articles)}")

# Browse articles by category
for article in articles:
    if "election" in article['title'].lower():
        print(f"Election article: {article['title']}")

🔍 Data Quality

✅ All articles sourced directly from Wikipedia
✅ Regular updates to maintain freshness
✅ Consistent JSON structure
✅ UTF-8 encoding
✅ Preserved section hierarchy
✅ Complete metadata

📜 Citation

@dataset{deepresearch_wiki_data_2024,
  title={DeepResearch Wiki Data},
  author={DeepResearch Team},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Looogic/DeepResearch_wiki_data},
  note={A comprehensive collection of Wikipedia articles about recent events (2023-2025)}
}

⚖️ License

This dataset is derived from Wikipedia content and is available under the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC BY-SA 3.0).

🔄 Updates

The dataset is regularly updated to include new events and developments. Check the commit history for the latest updates.

Built with 📚 for advancing factual AI research

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