Examples

To explore what's in ConceptNet, try browsing what it knows about any of these terms:

Word vectors and recent publications

ConceptNet is used to create word embeddings -- representations of word meanings as vectors, similar to word2vec, GloVe, or fastText, but better.

These word embeddings are free, multilingual, aligned across languages, and designed to avoid representing harmful stereotypes. Their performance at word similarity, within and across languages, was shown to be state of the art at SemEval 2017.

The process for learning these word vectors is described in our AAAI 2017 paper, which also shows state-of-the-art results on solving analogy problems.

Support and discussion

Detailed documentation about ConceptNet appears on its GitHub wiki.

You can chat with ConceptNet developers and users on Gitter, or join the conceptnet-users mailing list.

Updates to ConceptNet and its supporting technologies appear on the ConceptNet blog.

Linked Open Data API

ConceptNet is a proud part of the ecosystem of Linked Open Data.

As a modern Linked Open Data resource, the data in ConceptNet is available in a JSON-LD API, a format that aims to make linked data easy to understand and easy to work with. If you don't care what JSON-LD is, it's just a JSON REST API with some extra metadata.

You can use ExternalURL links in ConceptNet to find the same terms in other vocabularies, such as WordNet, DBPedia, and OpenCyc, which can provide you with other forms of information.

For information on how to use the ConceptNet API, see the API documentation. Or just start browsing it and you'll probably figure it out.