Group items tagged

WordNet® is a large lexical database of English, developed under the direction of George A. Miller. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic and lexical relations. The resulting network of meaningfully related words and concepts can be navigated with the browser. WordNet is also freely and publicly available for download. WordNet's structure makes it a useful tool for computational linguistics and natural language processing.

MultiWordNet is a multilingual lexical database in which the Italian WordNet is strictly aligned with Princeton WordNet 1.6.

a standard conversation of Princeton WorldNet to RDF/OWL

GeoWordNet is a semantic resource built from the full integration of WordNet, GeoNames and the Italian part of MultiWordNet.

Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicon. SUMO is written in the SUO-KIF language. SUMO is free and owned by the IEEE. The ontologies that extend SUMO are available under GNU General Public License. Adam Pease is the Technical Editor of SUMO.

The Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicon. SUMO is written in the SUO-KIF language. SUMO is free and owned by the IEEE. The ontologies that extend SUMO are available under GNU General Public License. Adam Pease is the Technical Editor of SUMO.

UBY is a large-scale lexical-semantic resource for natural language processing (NLP) based on the ISO standard Lexical Markup Framework (LMF). UBY combines a wide range of information from expert-constructed and collaboratively constructed resources for English and German. Currently, UBY holds structurally and semantically interoperable versions of nine resources in two languages:  English WordNet, Wiktionary, Wikipedia, FrameNet and VerbNet,  German Wikipedia, Wiktionary and GermaNet, and multilingual OmegaWiki. 

YAGO2 is a huge semantic knowledge base, derived from Wikipedia, WordNet and GeoNames. Currently, YAGO2 has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities.

"YAGO2s is a huge semantic knowledge base, derived from Wikipedia WordNet and GeoNames. Currently, YAGO2s has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities."

"The Suggested Upper Merged Ontology (SUMO) and its domain ontologies form the largest formal public ontology in existence today. They are being used for research and applications in search, linguistics and reasoning. SUMO is the only formal ontology that has been mapped to all of the WordNet lexicon. SUMO is written in the SUO-KIF language. SUMO is free and owned by the IEEE. The ontologies that extend SUMO are available under GNU General Public License. Adam Pease is the Technical Editor of SUMO."

YAGO is a huge semantic knowledge base, derived from Wikipedia and WordNet. YAGO knows more than 2 million entities (e.g. persons, organizations, cities), and 20 million facts about these entities. Unlike many other automatically assembled knowledge bases, YAGO has a manually confirmed accuracy of 95%.

Semantic matching is a type of ontology matching technique that relies on semantic information encoded in lightweight ontologies to identify nodes that are semantically related. Given any two graph-like structures, like classifications, database or XML schemas and ontologies, matching is an operator that identifies those nodes in the two structures which semantically correspond to one another. For example, applied to file systems it can identify that a folder labeled "car" is semantically equivalent to another folder "automobile" because they are synonyms in English. This information can be taken from a linguistic resource like WordNet.