dwb2023/gdelt-rag-sources-v4

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.