Datasets:

dwb2023
/

gdelt-gkg-2025-v2

	---
	license: cc-by-4.0
	tags:
	- text
	- news
	- global
	- knowledge-graph
	- geopolitics
	dataset_info:
	features:
	- name: GKGRECORDID
	dtype: string
	- name: DATE
	dtype: string
	- name: SourceCollectionIdentifier
	dtype: string
	- name: SourceCommonName
	dtype: string
	- name: DocumentIdentifier
	dtype: string
	- name: V1Counts
	dtype: string
	- name: V2.1Counts
	dtype: string
	- name: V1Themes
	dtype: string
	- name: V2EnhancedThemes
	dtype: string
	- name: V1Locations
	dtype: string
	- name: V2EnhancedLocations
	dtype: string
	- name: V1Persons
	dtype: string
	- name: V2EnhancedPersons
	dtype: string
	- name: V1Organizations
	dtype: string
	- name: V2EnhancedOrganizations
	dtype: string
	- name: V1.5Tone
	dtype: string
	- name: V2.1EnhancedDates
	dtype: string
	- name: V2GCAM
	dtype: string
	- name: V2.1SharingImage
	dtype: string
	- name: V2.1Quotations
	dtype: string
	- name: V2.1AllNames
	dtype: string
	- name: V2.1Amounts
	dtype: string
	---

	# Dataset Card for dwb2023/gdelt-gkg-2025-v2

	## Dataset Details

	### Dataset Description

	This dataset contains GDELT Global Knowledge Graph (GKG) data covering February 2025. It captures global event interactions, actor relationships, and contextual narratives to support temporal, spatial, and thematic analysis.

	- Curated by: dwb2023

	### Dataset Sources

	- Repository: [http://data.gdeltproject.org/gdeltv2](http://data.gdeltproject.org/gdeltv2)
	- GKG Documentation: [GDELT 2.0 Overview](https://blog.gdeltproject.org/gdelt-2-0-our-global-world-in-realtime/), [GDELT GKG Codebook](http://data.gdeltproject.org/documentation/GDELT-Global_Knowledge_Graph_Codebook-V2.1.pdf)

	## Uses

	### Direct Use

	This dataset is suitable for:

	- Temporal analysis of global events

	### Out-of-Scope Use

	- Not designed for real-time monitoring due to its historic and static nature
	- Not intended for medical diagnosis or predictive health modeling

	## Dataset Structure

	### Features and Relationships

	- this dataset focuses on a subset of features from the source GDELT dataset.

	\| Name \| Type \| Aspect \| Description \|
	\|------\|------\|---------\|-------------\|
	\| DATE \| string \| Metadata \| Publication date of the article/document \|
	\| SourceCollectionIdentifier \| string \| Metadata \| Unique identifier for the source collection \|
	\| SourceCommonName \| string \| Metadata \| Common/display name of the source \|
	\| DocumentIdentifier \| string \| Metadata \| Unique URL/identifier of the document \|
	\| V1Counts \| string \| Metrics \| Original count mentions of numeric values \|
	\| V2.1Counts \| string \| Metrics \| Enhanced numeric pattern extraction \|
	\| V1Themes \| string \| Classification \| Original thematic categorization \|
	\| V2EnhancedThemes \| string \| Classification \| Expanded theme taxonomy and classification \|
	\| V1Locations \| string \| Entities \| Original geographic mentions \|
	\| V2EnhancedLocations \| string \| Entities \| Enhanced location extraction with coordinates \|
	\| V1Persons \| string \| Entities \| Original person name mentions \|
	\| V2EnhancedPersons \| string \| Entities \| Enhanced person name extraction \|
	\| V1Organizations \| string \| Entities \| Original organization mentions \|
	\| V2EnhancedOrganizations \| string \| Entities \| Enhanced organization name extraction \|
	\| V1.5Tone \| string \| Sentiment \| Original emotional tone scoring \|
	\| V2.1EnhancedDates \| string \| Temporal \| Temporal reference extraction \|
	\| V2GCAM \| string \| Sentiment \| Global Content Analysis Measures \|
	\| V2.1SharingImage \| string \| Content \| URL of document image \|
	\| V2.1Quotations \| string \| Content \| Direct quote extraction \|
	\| V2.1AllNames \| string \| Entities \| Comprehensive named entity extraction \|
	\| V2.1Amounts \| string \| Metrics \| Quantity and measurement extraction \|

	### Aspects Overview:
	- Metadata: Core document information
	- Metrics: Numerical measurements and counts
	- Classification: Categorical and thematic analysis
	- Entities: Named entity recognition (locations, persons, organizations)
	- Sentiment: Emotional and tone analysis
	- Temporal: Time-related information
	- Content: Direct content extraction

	## Dataset Creation

	### Curation Rationale
	This dataset was curated to capture the rapidly evolving global narrative during February 2025. By zeroing in on this critical period, it offers a granular perspective on how geopolitical events, actor relationships, and thematic discussions shifted amid the escalating pandemic. The enhanced GKG features further enable advanced entity, sentiment, and thematic analysis, making it a valuable resource for studying the socio-political and economic impacts of emergent LLM capabilities.

	### Curation Approach
	A targeted subset of GDELT’s columns was selected to streamline analysis on key entities (locations, persons, organizations), thematic tags, and sentiment scores—core components of many knowledge-graph and text analytics workflows. This approach balances comprehensive coverage with manageable data size and performance. The ETL pipeline used to produce these transformations is documented here:
	[https://gist.github.com/donbr/5293468436a1a39bd2d9f4959cbd4923](https://gist.github.com/donbr/5293468436a1a39bd2d9f4959cbd4923).

	## Citation

	When using this dataset, please cite both the dataset and original GDELT project:

	```bibtex
	@misc{gdelt-gkg-2025-v2,
	title = {GDELT Global Knowledge Graph 2025 Dataset},
	author = {dwb2023},
	year = {2025},
	publisher = {Hugging Face},
	url = {https://huggingface.co/datasets/dwb2023/gdelt-gkg-2025-v2}
	}
	```

	## Dataset Card Contact

	For questions and comments about this dataset card, please contact dwb2023 through the Hugging Face platform.