An Overview of Nouns in WordNet v3.1 --- A Lexical Ontology

An Overview of Nouns in WordNet v3.1 ---A Lexical Ontology Xiangqian Lee Websoft Research Group

Content • Introduction • What is it? • Creators & History • Constitutions • Nouns in WordNet • Specific Relations • Overview • A Lexical Ontology • Back To WordNet

Introduction / What is it • What is it? • A large lexical database of English • Combination of dictionary and thesaurus • Aim to build a realistic model of English words and semantic relations between them from a psychological perspective. • Can be used for Text Analysis and AI applications • BSD style lisense. It can be freely downloaded and used.

Introduction / Creators & History the 2006 Antonio Zampolli Prize George A. Miller died in 2012, 92 years old Latest Online Version: WordNet 3.1 with WordNet leader Cognitive Science Lab Christiane Fellbaum released George A. Miller awarded started by 2012.11 2006 1985

Introduction / Constitutions • Basic Unit in WordNet: • Synset(Synonym set): One synset contains several words and represent a sense of meaning (or one concept in human's mind). • A word may have multiple meanings, so there may be several synsets containing it. • E.g. for word "research": n.{research} systematic investigation to establish facts n. {inqury, enqury, research} a search for knowledge v. {research, search, explore} inqury into v.{research} attempt to find out in a systematically and scientific manner

Introduction / Constitutions Total 117,762 synsets.

Introduction / Constitutions • Semantic Relations • There are different kinds of relations between concepts. • X is a kind of Y • X has part Y • X is Y • X has inverse meaning of Y • Examples:Synset {research (systematic investigation to establish facts)} Hypernym/Hyponym Holonym/Meronym Attribute Antonym . . . . . . n.{ marketing research, market research} research that gathers and analyzes information about the moving of good or services from producer to consumer n.{research} systematic investigation to establish facts is kind of hypernym is kind of n.{research} systematic investigation to establish facts n.{investigation, investigating} the work of inquiring into something thoroughly and systematically hyponym

Introduction / Constitutions • 2 kinds of relations: synset-to-synset, word-to-word • Synsets of different POS have different POS-specific relations. hyponym, hypernym, antonym, domain of synset, member of domain, derivationally related form,... Common Relations Adjective-specific relations Verb-specific relations Pertainym (pertains to noun) , participle to verb, similar to, also see,... entailment, cause, also see, verb group,... ......

Introduction / Constitutions • If we treat synsets as the nodes, the relations as the edges, we get a semantic graph. • The graph is sparse. Synsets of different POS have few relations, e.g • derivationally related form • topical domain of synset/member of domain • Attribute One limitation of WordNet [Christiane Fellbaum]

Nouns in WordNet / Specific Relations • Noun-specific relations: • Instance hypernym/instance hyponym: X is an instance of Y. • Memonym/Holonym: X is part of Y, e.g • Attribute: e.g n.{ racing car,race car, racer} is part of n.{ cockpit} memonym attribute adj.{ western} n.{ west, western United States} attribute

Nouns in WordNet / Specific Relations • Instance Hyponym/Instance Hypernym • Some synsets of nouns are not a concept or a type. They are instances of one concept or type. • In most cases, the instance synsets are terminal nodes.They have no hyponyms.In some rare cases, a synset can be a concept while is an instance of another concept. n.{city,metropolis,urban_center} a large and densely populated urban area ; may include several .... n.{Nanjing, Nanking} a city in eastern China on the Yangtze River ; a former capital of China ;... is an instance of instance hypernym n.{Oceanus} is an instance of is an instance of n.{Titan} n.{Greek_deity} is kind of hypernym n.{Epimetheus}

Nouns in WordNet / Overview • Noun synsets are put into 25 categories and a special category----Tops.

Nouns in WordNet / Overview • There are 7,742 synsets of nouns that can be an instance.

Nouns in WordNet / Overview • Since version 2.1, the creator adds a new category---Tops. All synsets are hyponyms of one synset {entity}. • Noun synsets as nodes, hyponym/instance hyponym as edges. We can get a DAG. All nodes are weakly conncected. network diameter: 18 Average length of path: 4.781 Average Degree: 1.028 {entity} {abstraction,abstract_entity} {physical_entity} {thing} . . . . . . Tops Noun.location Noun.person . . . . . .

Nouns in WordNet / A Lexical Ontology • Designing noun synsets in WordNet as a inheritance system has many supports from psycholinguistic evidences.[Quillian (1967, 1968)] • S1: "A canary can sing" • S2: "A canary can fly" • S3: "A canary has skin" • How fast can people respond true pr false of these statements? • Experiments shows: response time: S1 < S2 < S3 • "can sing" canary itself • "can fly" a bird a canary is a bird. • "has skin" a vertebrate a canary is a bird & a bird is one kind of a vertebrate. • This shows the features of one concept or instance is not stored redundantly but is retrieved when needed [Collins and Quillian]. It's widely accepted that English nouns are stored in a hierarchy.But it may be not true for words of other POS. • In WordNet, the hierarchy is: canary@→finch@→passerine@→bird@→vertebrate@→animal feature of based on feature of feature of based on

Nouns in WordNet / A Lexical Ontology • WordNet is a lexical ontology ( since v2.1). • WordNet has been mapped into formal ontologies • e.g SUMO[1], MILO[2] • Formal ontology may be the interlingua for cross linguistic wordnets [1]Niles, Ian, and A. Pease. Mapping WordNet to the SUMO ontology. Teknowledge Technical Report, 2003. [2]Niles, Ian, and Allan Terry. "The MILO: A General-purpose, Mid-level Ontology." In IKE, vol. 4, pp. 15-19. 2004.

Back to WordNet • WordNet is widely used in Ontology matching. • WordNet-based semantic similarity metrics[1] • Edge-based methods [2][3][4] • Information-based statistics methods [5][6] • Hybrid methods [7][8][9] [1]Lin, Feiyu, and Kurt Sandkuhl. A survey of exploiting wordnet in ontology matching. In Artificial Intelligence in Theory and Practice II, pp. 341-350. Springer US, 2008. [2]Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: 32nd. Annual Meeting of theAssociation for Computational Linguistics, pp. 133 –138. New Mexico State University, LasCruces, New Mexico (1994) [3]Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: IJCAI,pp. 448–453 (1995) [4]Su, X.: Semantic enrichment for ontology mapping. Ph.D. thesis, Dept. of Computer and Information Science, Norwegian University of Science and Technology (2004) [5]Resnik, P.: Semantic similarity in a taxonomy: An information-based measure and its application to problems of ambiguity in natural language. Journal of Artificial Intelligence Research 11, 95–130 (1999) [6]Lin, D.: An information-theoretic definition of similarity. In: Proc. 15th International Conf. on Machine Learning, pp. 296–304. Morgan Kaufmann, San Francisco, CA (1998) [7]Rodriguez, M., Egenhofer, M.: Determining semantic similarity among entity classes fromdifferent ontologies. IEEE Transactions on Knowledge and Data Engineering15(2), 442–456(2003) [8]Jiang, J.J., Conrath, D.W.: Semantic similarity based on corpus statistics and lexical taxonomy(1997) [9]Euripides G.M. Petrakis Giannis Varelas, A.H.P.R.: Design and evaluation of semantic similarity measures for concepts stemming from the same or different ontologies. In: In 4th Workshop on Multimedia Semantics (WMS’06), pp. 44–52 (2006)

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An Overview of Nouns in WordNet v3.1 --- A Lexical Ontology