Empirical Foundational Ontology of Common Sense

An empirically-grounded foundational ontology aimed at providing machines with the common sense knowledge used everyday by humans.

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Resources

FOX Metamodel

The metamodel of the foundational ontology

Datasets

Human- and machine-created datasets capturing the common sense

SPARQL Endpoint

A SPARQL endpoint containing all FOX data
(coming soon!)

FOX Live

A service that allows you to explore FOX
(coming soon!)

Datasets

The datasets constituting the foundational ontology of common sense are provided in RDF format and released under license CC-BY 4.0, except where otherwise stated. The datasets can be requested by compiling this form (a better process to get the data will be ready soon).

Classes and Instances according to Experts

4502 DBpedia entities classified by two experts as either classes or instances with respect to the common sense intuition (cf. [1])
GET THE DATA

Classes and Instances according to the Crowd

4502 DBpedia entities classified by crowdsourced annotators as either classes or instances with respect to the common sense intuition (cf. [1])
GET THE DATA

Physical Objects and not Physical Objects according to Experts

4502 DBpedia entities classified by two experts as either physical objects or not physical objects with respect to the common sense intuition (cf. [1])
GET THE DATA

Physical Objects and not Physical Objects according to the Crowd

4502 DBpedia entities classified by two experts as either physical objects or not physical objects with respect to the common sense intuition (cf. [1])
GET THE DATA

Machine-created datasets

Coming soon!

News

  • 2018-07-18: The paper "Empirical Analysis of Foundational Distinctions in Linked Open Data" will be presented today at IJCAI-ECAI 2018.

Publications

For citing FOX in academic papers please use:

  1. Luigi Asprino, Valerio Basile, Paolo Ciancarini, Valentina Presutti. Empirical Analysis of Foundational Distinctions in Linked Open Data. In: Proceedings of the 27th International Joint Conference on Artificial Intelligence Main track (IJCAI), pages 3962-3969, 2018, DOI: 10.24963/ijcai.2018/551 BIB Results of the experiments available on Github


Other publications related to FOX:

  • Andrea Giovanni Nuzzolese, Aldo Gangemi, Valentina Presutti, Paolo Ciancarini. Encyclopedic Knowledge Patterns from Wikipedia Links. In: Proceedings of the 10th International Semantic Web Conference (ISWC), pages 520-536, 2011.
  • Aldo Gangemi, Andrea Giovanni Nuzzolese, Valentina Presutti, Francesco Draicchio, Alberto Musetti, and Paolo Ciancarini. Automatic typing of dbpedia entities. In: Proceedings of the 11th International Semantic Web Conference (ISWC), Part I, pages 65–81, 2012.
  • Andrea Giovanni Nuzzolese, Aldo Gangemi, Valentina Presutti, and Paolo Ciancarini. Towards the Natural Ontology of Wikipedia. In: Proceedings of 12th International Semantic Web Conference (ISWC), Posters & Demos Track, pages 273-276, 2013.

Contributors

Luigi Asprino

University of Bologna and STLab (ISTC-CNR)

Valentina Presutti

STLab (ISTC-CNR)

Aldo Gangemi

University of Bologna

Valerio Basile

University of Turin

Paolo Ciancarini

University of Bologna

Let's get in touch!

Please fill this form, if you are interested in common sense knowledge, if you want to contribute to pursuing the objective of building the foundational ontology of common sense, or if you want comment (or even criticize) this work.