README.md

metadata

license: apache-2.0
task_categories:
  - text-retrieval
  - question-answering
tags:
  - rag
  - gdelt
  - knowledge-graphs
  - retrieval
pretty_name: GDELT RAG Source Documents
size_categories:
  - n<1K

GDELT RAG Source Documents

Dataset Description

This dataset contains source documents extracted from the research paper "Talking to GDELT Through Knowledge Graphs" (arXiv:2503.07584v3). The documents are used as the knowledge base for a Retrieval-Augmented Generation (RAG) system focused on GDELT (Global Database of Events, Language, and Tone) analysis.

Dataset Summary

• Total Documents: 38 pages
• Source: Research paper on GDELT Knowledge Graphs
• Format: PDF pages with extracted text and metadata
• Use Case: RAG knowledge base for GDELT-related queries

Data Fields

• page_content (string): Extracted text content from the PDF page
• metadata (dict): Document metadata including:
  • title: Paper title
  • author: Paper authors
  • page: Page number
  • total_pages: Total pages in source document
  • file_path: Original file path
  • format: Document format (PDF)
  • producer, creator: PDF metadata
  • Other PDF metadata fields

Data Splits

This dataset contains a single split with all 38 documents.

Source Data

The source material is the research paper:

• Title: "Talking to GDELT Through Knowledge Graphs"
• Authors: Audun Myers, Max Vargas, Sinan G. Aksoy, Cliff Joslyn, Benjamin Wilson, Lee Burke, Tom Grimes
• arXiv ID: 2503.07584v3

Licensing

This dataset is released under the Apache 2.0 license.

Citation

If you use this dataset, please cite the original paper:

@article{myers2025talking,
  title={Talking to GDELT Through Knowledge Graphs},
  author={Myers, Audun and Vargas, Max and Aksoy, Sinan G and Joslyn, Cliff and Wilson, Benjamin and Burke, Lee and Grimes, Tom},
  journal={arXiv preprint arXiv:2503.07584},
  year={2025}
}

Dataset Creation

This dataset was created as part of the AI Engineering Bootcamp Cohort 8 certification challenge project.