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The IEEE Standard Upper Ontology (IEEE, 2001) is an effort to create a large, general-purpose, formal ontology. The ontology will be an open standard that can be reused for both academic and commercial purposes without fee, and it will be designed to support additional domain-specific ontologies. The effort is targeted for use in automated inference, semantic interoperability between heterogeneous information systems and natural language processing applications. The effort was begun in May 2000 with an e-mail discussion list, and since then there have been over 6000 e-mail messages among 170 subscribers. These subscribers include representatives from government, academia and industry in various countries. The effort was officially approved as an IEEE standards project in December 2000. Recently a successful workshop was held at IJCAI 2001 to discuss progress and proposals for this project (IJCAI, 2001).

Ontologies are becoming more and more popular as background knowledge for intelligent applications. Up to now, there has been a schism between manually assembled, highly axiomatic ontologies and large, automatically constructed knowledge bases. This paper discusses how the two worlds can be brought together by combining the high-level axiomatizations from the Standard Upper Merged Ontology (SUMO) with the extensive world knowledge of the YAGO ontology. The result is a new large-scale formal ontology, which provides information about millions of entities such as people, cities, organizations, and companies

WordNet 1 is a large lexical database for English. With its broad coverage and a design that is useful for a range of natural-language processing applications, this resource has found wide general acceptance. We offer only a brief description here and refer the reader to Miller, 1990 and Fellbaum, 1998 for further details. WordNet's creation in the mid-1980s was motivated by current theories of human semantic organization (Collins and Quillian, 1969). People have knowledge about tens of thousands of concepts, and the words expressing these concepts must be stored and retrieved in an efficient and economic fashion. A semantic network such as WordNet is an attempt to model one way in which concepts and words could be organized.The basic unit of WordNet is a set of cognitively equivalent synonyms, or synset. Examples of a noun, verb, and adjective synset are { vacation, holiday }, { close, shut }, and { soiled, dirty }, respectively. Each synset represents a concept, and each member of a synset encodes the same concept. Differently put, synset members are interchangeable in many contexts without changing the truth value of the context. Each synset also includes a definition, or 'gloss', and an illustrative sentence.The current version of WordNet (3.0) contains over 117,000 synsets that are organized into a huge semantic network. The synsets are interlinked by means of bidirectional semantic relations such as hyponymy, meronymy, and a number of entailment relations. For example, the relation between oak and tree is such that oak is encoded as a hyponym (subordinate) of tree and tree is encoded as a hypernym (superordinate) of oak. Leaf and trunk are meronyms (parts) of tree, their holonym. Meronyms are transitive, so linking leaf and trunk to tree means that oak (and beech and maple etc.) inherits leaf and trunk as parts by virtue of its relation to tree (Miller, 1990(Miller, , 1998. Concepts expressed by other parts of speech (verbs, adjectives) are interlinked by means of additional relations (Fellbaum, 1998).