Dataset Viewer
The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code: ConfigNamesError
Exception: ValueError
Message: Feature type 'Stringsa' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']
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 "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
).get_module()
^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 605, in get_module
dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 317, in _from_yaml_dict
yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2031, in _from_yaml_list
return cls.from_dict(from_yaml_inner(yaml_data))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1876, in from_dict
obj = generate_from_dict(dic)
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1463, in generate_from_dict
return {key: generate_from_dict(value) for key, value in obj.items()}
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1469, in generate_from_dict
raise ValueError(f"Feature type '{_type}' not found. Available feature types: {list(_FEATURE_TYPES.keys())}")
ValueError: Feature type 'Stringsa' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Hazards Dataset
This dataset contains comprehensive information about various hazards, including preparation, reaction, and recovery steps. It is designed for fine-tuning Large Language Models (LLMs) on safety and emergency response procedures.
Dataset Structure
The dataset is provided in a format compatible with the Hugging Face datasets library.
Features
hazard_type(string): The high-level category of the hazard (e.g., "Wildfire", "Active Shooter").phase(string): The phase of emergency management ("Prepare", "React", "Recover").audience(string): The target audience ("General", "Kids", "Elderly", "Pets", etc.).topic(string): The specific subject matter of the text chunk (e.g., "Evacuation Routes").content_raw(string): The exact text content extracted from the source PDF.action_items(list of strings): A list of actionable steps extracted from the text.sources(list of dicts): A list of sources/references found in the text, each with atitleandurl.source_file(string): The filename of the source PDF.page_ref(int): The page number in the source PDF.last_updated(date): The date the source file was last modified.vector(list of floats): A 384-dimensional vector embedding of the content.
Example
{
"hazard_type": "Avalanche",
"phase": "Recover",
"audience": "General",
"topic": "General Safety",
"content_raw": "A rapid flow of snow...",
"action_items": ["Stay calm", "Signal for help"],
"sources": [{"title": "Avalanche.org", "url": "https://avalanche.org"}],
"source_file": "avalanche.pdf",
"page_ref": 1,
"last_updated": "2025-11-24",
"vector": [0.023, -0.12, ...]
}
Creation Process
Data Source
The data is sourced from Hazadapt, a safety application providing guides for various hazards.
Collection Method
Data was collected using a custom pipeline that:
- Scrapes hazard pages and downloads official PDF guides using Playwright.
- Processes PDFs using
PyMuPDF4LLMto extract text and layout information. - Parses content into structured fields (Phase, Audience, Topic) using keyword heuristics and layout analysis.
- Embeds content using
sentence-transformers/all-MiniLM-L6-v2.
Intended Use
- LLM Fine-tuning: To train models on safety protocols and emergency response.
- RAG (Retrieval-Augmented Generation): As a knowledge base for safety chatbots.
- Analysis: For analyzing the structure and content of emergency guides.
Citation
If you use this dataset in your research or application, please cite it as follows:
@dataset{civilian-hazard-lifecycle-instruct,
author = {Uday Ramesh Phalak},
title = {Civilian Hazard Safety Dataset},
year = {2025}, month = nov,
publisher = {Uday Ramesh Phalak},
url = {https://huggingface.co/datasets/Uday/civilian-hazard-lifecycle-instruct}
}
Limitations
- Users should verify critical safety information with official sources.
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