Uday/civilian-hazard-lifecycle-instruct

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 a title and url.
• —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:

1. 1.Scrapes hazard pages and downloads official PDF guides using Playwright.
2. 2.Processes PDFs using PyMuPDF4LLM to extract text and layout information.
3. 3.Parses content into structured fields (Phase, Audience, Topic) using keyword heuristics and layout analysis.
4. 4.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.