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ConceptNet 5.x Raw Data

This archive contains the raw data that ConceptNet 5 is built from. More information about ConceptNet is available at http://conceptnet.io. If you use ConceptNet as part of another work, you must attribute ConceptNet and you must not restrict its license terms. For more license

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CreatorSpeer, Robyn
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Published2020-04-03
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DOI10.5281/zenodo.3739540
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Downloads21,383
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Licensecc-by-sa-4.0
File Size43.9 GB
Data TypeDataset
Published2020
Licensecc-by-sa-4.0
Total Views8,011
Total Downloads21,383

This archive contains the raw data that ConceptNet 5 is built from. More information about ConceptNet is available at http://conceptnet.io.

If you use ConceptNet as part of another work, you must attribute ConceptNet and you must not restrict its license terms. For more license information: https://creativecommons.org/licenses/by-sa/4.0/

ConceptNet has been developed by:

* The MIT Media Lab, through various groups at different times:

  – Commonsense Computing
  – Software Agents
  – Digital Intuition

* The Commonsense Computing Initiative, a worldwide collaboration with
  contributions from:

  – National Taiwan University
  – Universidade Federal de São Carlos
  – Hokkaido University
  – Tilburg University
  – Nihon Unisys Labs
  – Dentsu Inc.
  – Kyoto University
  – Yahoo Research Japan

* Luminoso Technologies, Inc.

Significant amounts of data were imported from:

* WordNet, a project of Princeton University
* Wikipedia and Wiktionary, collaborative projects of the Wikimedia Foundation
* Luis von Ahn's "Games with a Purpose"
* DBPedia
* OpenCyc
* JMDict, by Jim Breen

ConceptNet also takes input from these sources of distributional word embeddings:

ConceptNet takes input from these sources of pre-computed distributional word embeddings:

– GloVe: Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014. GloVe: Global Vectors for Word Representation.
 https://nlp.stanford.edu/projects/glove/

– word2vec: Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient Estimation of Word Representations in Vector Space. In Computing Research Repository. http://dblp.org/rec/bib/journals/corr/abs-1301-3781

– fastText: Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2016. Enriching Word Vectors with Subword Information. http://fasttext.cc
 

Here is a short, incomplete list of people who have made significant
contributions to the development of ConceptNet as a data resource, roughly in
order of appearance:

* Push Singh
* Catherine Havasi
* Hugo Liu
* Hyemin Chung
* Robyn Speer
* Ken Arnold
* Yen-Ling Kuo
* Naoki Otani
 

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ConceptNet 5.x Raw Data (Full Dataset)43.9 GB
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Files are hosted on the source repository. Click download to access the full dataset.

Speer, Robyn (2020). ConceptNet 5.x Raw Data. https://doi.org/10.5281/zenodo.3739540