Adam Pease

Towards a standard upper ontology

The Suggested Upper Merged Ontology (SUMO) is an upper levelontology that has been proposed as a starter document for TheStandard Upper Ontology Working Group, an IEEE-sanctioned workinggroup of collaborators from the fields of engineering, philosophy,and information science. The SUMO provides definitions forgeneral-purpose terms and acts as a foundation for more specificdomain ontologies. In this paper we outline the strategy used tocreate the current version of the SUMO, discuss some of thechallenges that we faced in constructing the ontology, and describein detail its most general concepts and the relations between them.

The DARPA High-Performance Knowledge Bases Project

Now completing its first year, the High-Performance Knowledge Bases Project promotes technology for developing very large, flexible, and reusable knowledge bases. The project is supported by the Defense Advanced Research Projects Agency and includes more than 15 contractors in universities, research laboratories, and companies. The evaluation of the constituent technologies centers on two challenge problems, in crisis management and battlespace reasoning, each demanding powerful problem solving with very large knowledge bases. This article discusses the challenge problems, the constituent technologies, and their integration and evaluation.

IEEE standard upper ontology: a progress report

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).

Ontology and the Lexicon: Formal ontology as interlingua: the SUMO and WordNet linking project and global WordNet

WordNet1 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, 1998). Concepts expressed by other parts of speech (verbs, adjectives) are interlinked by means of additional relations (Fellbaum, 1998).

Large theory reasoning with SUMO at CASC

The Suggested Upper Merged Ontology (SUMO) has provided the TPTP problem library with problems that have large numbers of axioms, of which typically only a few are needed to prove any given conjecture. The LTB division of the CADE ATP System Competition tests the performance of ATP systems on these types of problems. The SUMO problems were used in the SMO category of the LTB division in 2008. This paper presents an analysis of the performance of the 2007 and 2008 CASC entrants on the SUMO problems, illustrating the improvements that can be achieved by various tuning techniques.

Agent-Mediated Knowledge Engineering Collaboration

Knowledge Management is most necessary and valuable in a collaborative and distributed environment. A problem with commercial knowledge management tools is that they do not understand at a deep level the content that they are managing. In this paper we discuss the System for Collaborative Open Ontology Production (SCOOP), which manipulates logic expressions and checks for redundancies or contradictions between the products developed by different engineers. SCOOP also includes an automated workflow process that supports recommendations for changes and voting to agree on changes.

Higher-order aspects and context in SUMO

This article addresses the automation of higher-order aspects in expressive ontologies such as the suggested upper merged ontology SUMO. Evidence is provided that modern higher-order automated theorem provers like LEO-II can be fruitfully employed for the task. A particular focus is on embedded formulas (formulas as terms), which are used in SUMO, for example, for modeling temporal, epistemic, or doxastic contexts. This modeling is partly in conflict with SUMOs assumption of a bivalent, classical semantics and it may hence lead to counterintuitive reasoning results with automated theorem provers in practice. A solution is proposed that maps SUMO to quantified multimodal logic which is in turn modeled as a fragment of classical higher-order logic. This way automated higher-order theorem provers can be safely applied for reasoning about modal contexts in SUMO.Our findings are of wider relevance as they analogously apply to other expressive ontologies and knowledge representation formalisms.

Sigma: An integrated development environment for formal ontology

Sigma is an open source environment for the development of logical theories. It has been under development and regular release for nearly a decade, and has been the principal environment under which the open source Suggested Upper Merged Ontology SUMO has been created. We discuss its features and evolution, and explain why it is an appropriate environment for the development of expressive ontologies in first and higher order logic.

Controlled English to Logic Translation

The Controlled English to Logic (CELT) system translates a restricted English grammar to expressions in formal logic. The logic statements use terms from a large formal ontology, the Suggested Upper Merged Ontology (SUMO), giving each resulting statement a wealth of deep meaning, similar in kind if not in degree to capturing the meaning a human associates with words in context.

A Multilingual Lexico-Semantic Database and Ontology

We discuss the development of a multilingual lexicon linked to the Suggested Upper Merged Ontology (SUMO) formal ontology. The ontology as well as the lexicon have been expressed in Web Ontology Language (OWL), as well as their original formats, for use on the semantic web and in linked data. We describe the Open Multilingual Wordnet (OMW), a multilingual wordnet with 22 languages and a rich structure of semantic relations. It is made by exploiting links from various monolingual wordnets to the English Wordnet. Currently, it contains 118,337 concepts expressed in 1,643,260 senses in 22 languages. It is available as simple tab-separated files, Wordnet-Lexical Markup Framework (LMF) or lemon and had been used by many projects including BabelNet and Google Translate. We discuss some issues in extending the wordnets and improving the multilingual representation to cover concepts not lexicalized in English and how concepts are stated in the formal ontology.