GREED - GeRman Energy and Environment Document Corpus for Geoparsing and Time Expression Normalization Tasks

This dataset contains scientific texts with rich linguistic or structural annotations for research purposes.
It is designed to support tasks such as natural language processing, information extraction, and corpus linguistics.

Contents

The dataset consists of two main components:

1. Text Content
   Excerpts or full text passages from scientific publications. These were included with explicit permission from the respective authors or rights holders.

   The following table lists the included files and the corresponding source information:

⚠️ The individuals and institutions listed here are the copyright holders of the corresponding documents.
The text content is used with their permission and may only be used for non-commercial, scientific purposes.

2. Annotations
   Metadata, structural, or linguistic annotations created manually or semi-automatically, intended to support various forms of scientific analysis.

License

Annotations

All annotations and the dataset structure are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
You are free to use, modify, and redistribute the annotations — including for commercial purposes — provided that appropriate credit is given.

🔗 CC BY 4.0 Summary

Text Content

The original text content is copyrighted and included with permission from the respective authors or publishers.
It is made available exclusively for non-commercial, scientific use.

• ✅ Permitted: Academic research, teaching, citation in scientific publications.
• ❌ Not permitted: Commercial use, redistribution of raw text content outside of research settings, or adaptation beyond scholarly work.

For more details, refer to the LICENSE.txt file.

Author and Contact Information:

• Institution: Karlsruhe Institute of Technology (KIT), Institute for Automation and Applied Informatics (IAI)
• Main Author: Nicolas Doms, [email protected]
• Authors: Toni Golian, Ruidie Hu
• Principle Investigator: Thorsten Schlachter, [email protected]

Version and Date of Publication

• Version: 1.0
• Date: 2025-04-08

Disclaimer

This dataset is provided "as is" without warranty. The authors are not responsible for any misuse of the content. Users must ensure compliance with the licensing terms when distributing or using the dataset.

TagCombiner.py

Text content and annotations are delivered separately in this dataset to ensure a clear separation with regard to the license.
This dataset includes a Python file named TagCombiner.py. This simple code merges the tags from the "Tags" directory into the raw text data in the "Raw" directory.
The resulting files have the annotations in-line and can be used for the evaluation of machine learning models.