---
language:
- en
tags:
- knowledge-graph
- english
- relations
- conceptnet
pretty_name: ' Conceptnet Full EN [essentials]'
---

# Conceptnet Full EN (essentials)

## Dataset Summary:

This dataset is a compact and simplified version of ConceptNet, emphasizing English concepts and their sources. It retains the essential information about the relations in a format that is straightforward and user-friendly. Designed for efficiency and ease of use, this dataset is particularly suitable for scenarios with computational constraints. While the original ConceptNet database exceeds 20GB in size, this streamlined version is a mere 500MB, making it feasible to run on less powerful computers or servers without compromising the richness of English-centric knowledge.

## Motivation:

The genesis of this dataset lies in a comprehensive study aimed at enhancing the ability of AI systems to disambiguate English concepts. In the vast expanse of language, terms frequently adopt varied meanings depending on context, making it a daunting task for individuals to encompass all possible interpretations of a single term. ConceptNet, with its rich tapestry of relationships between concepts and their origins, provides a distinctive perspective to navigate and comprehend these layered meanings. By condensing this extensive knowledge repository into a more concise and accessible format, our analyses became not only swifter but also more resource-efficient. Recognizing the potential value to the broader community, we felt compelled to share this dataset openly.

## Dataset Structure
Before diving into the specific fields, it's essential to understand that each entry in this dataset captures a relationship. This relationship can be between two English concepts or between an English concept and its external source (URL). These relationships are detailed through a set of fields that provide both textual and URI-based identifiers, along with a weight that quantifies the relationship's strength or significance.

### Sample:
```plaintext
start_text:    areligious
relation_text: Antonym
end_text:      religious
start_uri:     /c/en/areligious/a
relation_uri:  /r/Antonym
end_uri:       /c/en/religious
weight:        1
```
### Fields:

- **start_text**: The textual representation of the starting concept in the relationship.

- **relation_text**: The textual description of the type of relationship, whether it's between two concepts or a concept and its source.

- **end_text**: The textual representation of the ending concept or the external URL in the relationship.

- **surfaceText**: A human-readable sentence or phrase that illustrates the relationship between the `start_text` and `end_text` concepts.

- **start_uri**: The unique URI identifier for the starting concept.

- **relation_uri**: The unique URI identifier for the type of relationship. This URI can be used to understand the nature of the relationship. For a comprehensive list of relation types and their meanings, refer to [ConceptNet's Relation Types Documentation](https://github.com/commonsense/conceptnet5/wiki/Relations).

- **end_uri**: The unique URI identifier for the ending concept or the external URL.

- **weight**: A numerical value representing the strength or significance of the relationship. The weight is derived from the number of sources that support the relationship and the reliability of these sources. A higher weight indicates a stronger consensus or more robust evidence for the relationship in the knowledge base.

**Note**: The dataset contains multiple self-looping relations. These were present in the original ConceptNet data, and the decision was made to retain them for this compact version.

## Licensing and Attribution

This dataset is released under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). Users are free to use, modify, and distribute the dataset, provided they give appropriate credit to the original source and indicate if changes were made. For proper attribution, please reference the original ConceptNet data and this compact version when utilizing it in your work.
## Acknowledgments

A heartfelt thank you goes out to the ConceptNet team for their invaluable work in creating a comprehensive knowledge base that serves as the foundation for this dataset. 

For academic purposes, we recommend citing the original ConceptNet work as follows:

```
Robyn Speer et al. ConceptNet 5. Available at: [ConceptNet GitHub Repository](https://github.com/commonsense/conceptnet5).
```

---

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