Wikipedia

WordNet

WordNetis alexical databaseofsemantic relationsbetweenwordsthat linkswordsintosemantic relationsincludingsynonyms,hyponyms,andmeronyms.The synonyms are grouped intosynsetswith short definitions and usage examples. It can thus be seen as a combination and extension of adictionaryandthesaurus.While it is accessible to human users via aweb browser,[2]its primary use is in automatictext analysisandartificial intelligenceapplications. It was first created in theEnglish language[3]and the English WordNetdatabaseandsoftwaretools have been released under aBSD style licenseand are freely available for download from that WordNet website. There are now WordNets in more than 200 languages.[4]

WordNet
Developer(s)Princeton University
Initial releasemid 1980s
Stable release
3.1 / June 2011;13 years ago(2011-06)[1]
Written inProlog
Operating systemUnix, Linux, Solaris, Windows
Size16MB (including 155,327 words organized in 175,979 synsets for a total of 207,016 word-sense pairs)
Available inMore than 200 languages
TypeLexical database
LicenceBSD-like
Websitewordnet.princeton.edu

History and team members

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WordNet was first created in 1985, in English only, in theCognitive ScienceLaboratory ofPrinceton Universityunder the direction ofpsychologyprofessorGeorge Armitage Miller.It was later directed byChristiane Fellbaum.The project was initially funded by the U.S. Office of Naval Research, and later also by other U.S. government agencies including theDARPA,theNational Science Foundation,theDisruptive Technology Office(formerly the Advanced Research and Development Activity) and REFLEX. George Miller and Christiane Fellbaum received the 2006 Antonio Zampolli Prize for their work with WordNet.

The Global WordNet Association is a non-commercial organization that provides a platform for discussing, sharing and connecting WordNets for all languages in the world.Christiane FellbaumandPiek Th.J.M. Vossenare its co-presidents.[5]

Database contents

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Example entry "Hamburger" in WordNet

The database contains 155,327 words organized in 175,979synsetsfor a total of 207,016 word-sense pairs; incompressedform, it is about 12megabytesin size.[6]

It includes the lexical categoriesnouns,verbs,adjectivesandadverbsbut ignoresprepositions,determinersand other function words.

Words from the same lexical category that are roughly synonymous are grouped intosynsets,which include simplex words as well ascollocationslike "eat out" and "car pool." The different senses of apolysemousword form are assigned to different synsets. A synset's meaning is further clarified with a short definingglossand one or more usage examples. An example adjective synset is:

good, right, ripe – (most suitable or right for a particular purpose; "a good time to plant tomatoes"; "the right time to act"; "the time is ripe for great sociological changes" )

All synsets are connected by means of semantic relations. These relations, which are not all shared by all lexical categories, include:

  • Nouns
    • hypernym:Yis a hypernym ofXif everyXis a (kind of)Y(canineis a hypernym ofdog)
    • hyponym:Yis a hyponym ofXif everyYis a (kind of)X(dogis a hyponym ofcanine)
    • coordinate term:Yis a coordinate term ofXifXandYshare a hypernym (wolfis a coordinate term ofdog,anddogis a coordinate term ofwolf)
    • holonym:Yis a holonym ofXifXis a part ofY(buildingis a holonym ofwindow)
    • meronym:Yis a meronym ofXifYis a part ofX(windowis a meronym ofbuilding)
  • Verbs
    • hypernym:the verbYis a hypernym of the verbXif the activityXis a (kind of)Y(to perceiveis an hypernym ofto listen)
    • troponym:the verbYis a troponym of the verbXif the activityYis doingXin some manner (to lispis a troponym ofto talk)
    • entailment:the verbYis entailed by the verbXif by doingXyou must be doingY(to sleepis entailed byto snore)
    • coordinate term:the verbYis a coordinate term of the verbXifXandYshare a hypernym (to lispis a coordinate term ofto yell,andto yellis a coordinate term ofto lisp)

These semantic relations hold among all members of the linked synsets. Individual synset members (words) can also be connected with lexical relations. For example, (one sense of) the noun "director" is linked to (one sense of) the verb "direct" from which it is derived via a "morphosemantic" link.

The morphology functions of the software distributed with the database try to deduce thelemmaorstemform of awordfrom the user's input. Irregular forms are stored in a list, and looking up "ate" will return "eat," for example.

Knowledge structure

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Both nouns and verbs are organized into hierarchies, defined byhypernymorIS Arelationships. For instance, one sense of the worddogis found following hypernym hierarchy; the words at the same level represent synset members. Each set of synonyms has a unique index.

  • dog, domestic dog, Canis familiaris
    • canine, canid
      • carnivore
        • placental, placental mammal, eutherian, eutherian mammal
          • mammal
            • vertebrate, craniate
              • chordate
                • animal, animate being, beast, brute, creature, fauna
                  • ...

At the top level, these hierarchies are organized into 25 beginner "trees" for nouns and 15 for verbs (calledlexicographic filesat a maintenance level). All are linked to a unique beginner synset, "entity". Noun hierarchies are far deeper than verb hierarchies.

Adjectives are not organized into hierarchical trees. Instead, two "central" antonyms such as "hot" and "cold" form binary poles, while 'satellite' synonyms such as "steaming" and "chilly" connect to their respective poles via a "similarity" relations. The adjectives can be visualized in this way as "dumbbells" rather than as "trees".

Psycholinguistic aspects

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The initial goal of the WordNet project was to build a lexical database that would be consistent with theories of human semantic memory developed in the late 1960s. Psychological experiments indicated that speakers organized their knowledge of concepts in an economic, hierarchical fashion. Retrieval time required to access conceptual knowledge seemed to be directly related to the number of hierarchies the speaker needed to "traverse" to access the knowledge. Thus, speakers could more quickly verify thatcanaries can singbecause a canary is a songbird, but required slightly more time to verify thatcanaries can fly(where they had to access the concept "bird" on the superordinate level) and even more time to verifycanaries have skin(requiring look-up across multiple levels of hyponymy, up to "animal" ).[7] While suchpsycholinguisticexperiments and the underlying theories have been subject to criticism, some of WordNet's organization is consistent with experimental evidence. For example,anomic aphasiaselectively affects speakers' ability to produce words from a specific semantic category, a WordNet hierarchy. Antonymous adjectives (WordNet's central adjectives in the dumbbell structure) are found to co-occur far more frequently than chance, a fact that has been found to hold for many languages.

As a lexical ontology

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WordNet is sometimes called an ontology, a persistent claim that its creators do not make. The hypernym/hyponym relationships among the noun synsets can be interpreted as specialization relations among conceptual categories. In other words, WordNet can be interpreted and used as a lexicalontologyin thecomputer sciencesense. However, such an ontology should be corrected before being used, because it contains hundreds of basic semantic inconsistencies; for example there are, (i) common specializations for exclusive categories and (ii) redundancies in the specialization hierarchy. Furthermore, transforming WordNet into a lexical ontology usable for knowledge representation should normally also involve (i) distinguishing the specialization relations intosubtypeOfandinstanceOfrelations, and (ii) associating intuitive unique identifiers to each category. Although such corrections and transformations have been performed and documented as part of the integration of WordNet 1.7 into the cooperatively updatable knowledge base of WebKB-2,[8]most projects claiming to reuse WordNet for knowledge-based applications (typically, knowledge-oriented information retrieval) simply reuse it directly.

WordNet has also been converted to a formal specification, by means of a hybrid bottom-up top-down methodology to automatically extract association relations from it and interpret these associations in terms of a set of conceptual relations, formally defined in theDOLCE foundational ontology.[9]

In most works that claim to have integrated WordNet into ontologies, the content of WordNet has not simply been corrected when it seemed necessary; instead, it has been heavily reinterpreted and updated whenever suitable. This was the case when, for example, the top-level ontology of WordNet was restructured[10]according to theOntoClean-based approach, or when it was used as a primary source for constructing the lower classes of the SENSUS ontology.

Limitations

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The most widely discussed limitation of WordNet (and related resources likeImageNet) is that some of thesemantic relationsare more suited to concrete concepts than to abstract concepts.[11]For example, it is easy to create hyponyms/hypernym relationships to capture that a "conifer"is a type of"tree",a" tree "is a type of"plant",and a" plant "is a type of"organism",but it is difficult to classify emotions like" fear "or" happiness "into equally deep and well-defined hyponyms/hypernym relationships.

Many of the concepts in WordNet are specific to certain languages and the most accurate reported mapping between languages is 94%.[12]Synonyms, hyponyms, meronyms, and antonyms occur in all languages with a WordNet so far, but other semantic relationships are language-specific.[13]This limits the interoperability across languages. However, it also makes WordNet a resource for highlighting and studying the differences between languages, so it is not necessarily a limitation for all use cases.

WordNet does not include information about theetymologyor the pronunciation of words and it contains only limited information about usage. WordNet aims to cover most everyday words and does not include much domain-specific terminology.

WordNet is the most commonly used computational lexicon of English forword-sense disambiguation(WSD), a task aimed at assigning the context-appropriate meanings (i.e. synset members) to words in a text.[14]However, it has been argued that WordNet encodes sense distinctions that are too fine-grained. This issue prevents WSD systems from achieving a level of performance comparable to that of humans, who do not always agree when confronted with the task of selecting a sense from a dictionary that matches a word in a context. The granularity issue has been tackled by proposingclusteringmethods that automatically group together similar senses of the same word.[15][16][17]

Offensive content

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WordNet includes words that can be perceived aspejorativeor offensive.[18]The interpretation of a word canchange over timeandbetween social groups,so it is not always possible for WordNet to define a word as "pejorative"or" offensive "in isolation. Therefore, people using WordNet must apply their own methods to identify offensive or pejorative words.

However, this limitation is true of other lexical resources likedictionariesandthesauruses,which also containpejorativeand offensive words. Some dictionaries indicate words that arepejoratives,but do not include all the contexts in which words might be acceptable or offensive to different social groups. Therefore, people using dictionaries must apply their own methods to identify all offensive words.

Licensed vs. Open WordNets

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Some wordnets were subsequently created for other languages. A 2012 survey lists the wordnets and their availability.[19]In an effort to propagate the usage of WordNets, the Global WordNet community had been slowly re-licensing their WordNets to an open domain where researchers and developers can easily access and use WordNets as language resources to provideontologicalandlexicalknowledge innatural-language processing(NLP) tasks.

The Open Multilingual WordNet[20]provides access toopen licensedwordnets in a variety of languages, all linked to the Princeton Wordnet of English (PWN). The goal is to make it easy to use wordnets in multiple languages.

Applications

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WordNet has been used for a number of purposes in information systems, includingword-sense disambiguation,information retrieval,automatic text classification,automatic text summarization,machine translationand even automatic crossword puzzle generation.

A common use of WordNet is to determine thesimilaritybetween words. Various algorithms have been proposed, including measuring the distance among words and synsets in WordNet's graph structure, such as by counting the number of edges among synsets. The intuition is that the closer two words or synsets are, the closer their meaning. A number of WordNet-based word similarity algorithms are implemented in aPerlpackage called WordNet::Similarity,[21]and in aPythonpackage calledNLTK.[22]Other more sophisticated WordNet-based similarity techniques include ADW,[23]whose implementation is available inJava.WordNet can also be used to inter-link other vocabularies.[24]

Interfaces

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Princeton maintains a list of related projects[25]that includes links to some of the widely usedapplication programming interfacesavailable for accessing WordNet using various programming languages and environments.

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WordNet is connected to several databases of theSemantic Web.WordNet is also commonly reused via mappings between the WordNet synsets and the categories from ontologies. Most often, only the top-level categories of WordNet are mapped.

Global WordNet Association

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The Global WordNet Association (GWA)[26]is a public and non-commercial organization that provides a platform for discussing, sharing and connecting wordnets for all languages in the world. The GWA also promotes the standardization of wordnets across languages, to ensure its uniformity in enumerating the synsets in human languages. The GWA keeps a list of wordnets developed around the world.[27]

Other languages

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  • Arabic WordNet:[28][29]WordNet for Arabic language.
  • Arabic Ontology,a linguistic ontology that has the same structure as wordnet, and mapped to it.
  • The BalkaNet project[30]has produced WordNets for six European languages (Bulgarian, Czech, Greek, Romanian, Turkish and Serbian). For this project, a freely available XML-based WordNet editor was developed. This editor – VisDic – is not in active development anymore, but is still used for the creation of various WordNets. Its successor, DEBVisDic, is client-server application and is currently used for the editing of several WordNets (Dutch in Cornetto project, Polish, Hungarian, several African languages, Chinese).
  • BulNetis a Bulgarian version of the WordNet developed at the Department of Computational Linguistics of theInstitute for Bulgarian Language,Bulgarian Academy of Sciences.[31]
  • CWN (Chinese Wordnet or trung văn từ hối võng lộ ) supported byNational Taiwan University.[32]
  • TheEuroWordNetproject[33]has produced WordNets for several European languages and linked them together; these are not freely available however. The Global Wordnet project attempts to coordinate the production and linking of "wordnets" for all languages.[34]Oxford University Press,the publisher of theOxford English Dictionary,has voiced plans to produce their own online competitor to WordNet.[citation needed]
  • FinnWordNet is a Finnish version of the WordNet where all entries of the original English WordNet were translated.[35]
  • GermaNetis a German version of the WordNet developed by the University of Tübingen.[36]
  • TheIndoWordNet[37]is a linked lexical knowledge base of wordnets of 18 scheduled languages of India viz.,Assamese,Bangla,Bodo,Gujarati,Hindi,Kannada,Kashmiri,Konkani,Malayalam,Meitei(Manipuri),Marathi,Nepali,Odia,Punjabi,Sanskrit,Tamil,TeluguandUrdu.
  • JAWS (Just Another WordNet Subset), another French version of WordNet[38]built using the Wiktionary and semantic spaces
  • WordNet Bahasa:WordNet for Malay and Indonesia language, developed byNanyang University of Technology.
  • Malayalam WordNet,developed byCochin University Of Science and Technology.[39]
  • Multilingual Central Repository (MCR) integrates in the same EuroWordNet framework wordnets from Spanish, Catalan, Basque, Galician and Portuguese liked to English.[40]
  • The MultiWordNet project,[41]a multilingual WordNet aimed at producing an Italian WordNet strongly aligned with the Princeton WordNet.
  • OpenDutchWordNet,[42]is a Dutch lexical semantic database.
  • OpenWN-PT is a Brazilian Portuguese version of the original WordNet freely available for download under CC-BY-SA license.[43]
  • plWordNet[44]is a Polish-language version of WordNet developed byWrocław University of Technology.
  • PolNet[45]is a Polish-language version of WordNet developed byAdam Mickiewicz University in Poznań(distributed under CC BY-NC-ND 3.0 license).

Projects such as BalkaNet and EuroWordNet made it feasible to create standalone wordnets linked to the original one. Two such projects were the Russian WordNet, patronized byPetersburg State University of Means of Communication[46]and led by S.A. Yablonsky,[47]and Russnet,[48]bySaint Petersburg State University.

  • UWN is an automatically constructed multilingual lexical knowledge base extending WordNet to cover over a million words in many different languages.[49]
  • WOLF (WordNet Libre du Français), a French version of WordNet.[50]

Linked data

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  • BabelNet,[51]a very large multilingualsemantic networkwith millions of concepts obtained by integrating WordNet and Wikipedia using an automatic mapping algorithm.
  • TheSUMOontology[52]has a complete manual mapping[1][53]between all of the WordNet synsets and all of SUMO (including its domain ontologies, when WordNet contains a word sense for a given SUMO term) which is browsable at, for example[2].
  • OpenCyc,[54]an openontologyandknowledge baseof everyday common sense knowledge, has 12,000 terms linked to WordNet synonym sets.
  • DOLCE,[55]is the first module of the WonderWeb Foundational Ontologies Library (WFOL). This upper-ontology has been developed in light of rigorous ontological principles inspired by the philosophical tradition, with a clear orientation toward language and cognition. OntoWordNet[56]is the result of an experimental alignment of WordNet's upper level with DOLCE. It is suggested that such alignment could lead to an "ontologically sweetened" WordNet, meant to be conceptually more rigorous, cognitively transparent, and efficiently exploitable in several applications.
  • DBpedia,[57]a database of structured information, is linked to WordNet.
  • TheeXtended WordNet[58]is a project at theUniversity of Texas at Dallaswhich aims to improve WordNet by semantically parsing the glosses, thus making the information contained in these definitions available for automatic knowledge processing systems. It is freely available under a license similar to WordNet's.
  • TheGCIDEproject produced a dictionary by combining apublic domainWebster's Dictionaryfrom 1913 with some WordNet definitions and material provided by volunteers. It was released under thecopyleftlicenseGPL.
  • ImageNetis an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by millions of images.[59]Currently, it has over 500 images per node on average.
  • BioWordnet, a biomedical extension of wordnet was abandoned due to issues about stability over versions.[60]
  • WikiTax2WordNet, a mapping between WordNet synsets andWikipedia categories.[61]
  • WordNet++, a resource including over millions of semantic edges harvested from Wikipedia and connecting pairs of WordNet synsets.[62]
  • SentiWordNet, a resource for supporting opinion mining applications obtained by tagging all the WordNet 3.0 synsets according to their estimated degrees of positivity, negativity, and neutrality.[63]
  • ColorDict, is an Android application to mobiles phones that use Wordnet database and others, like Wikipedia.
  • UBY-LMFa database of 10 resources including WordNet.
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  • FrameNetis a lexical database that shares some similarities with, and refers to, WordNet.
  • Lexical markup framework(LMF) is an ISO standard specified withinISO/TC37in order to define a common standardized framework for the construction of lexicons, including WordNet. The subset of LMF for Wordnet is called Wordnet-LMF. An instantiation has been made within the KYOTO project.[64]
  • UNL Programmeis a project under the auspices ofUNOaimed to consolidate lexicosemantic data of many languages to be used in machine translation andinformation extractionsystems.
  • Meaning Monkeyis a free online dictionary based on the WordNet database.
  • Dictionary.videois a video dictionary focusing on pronunciations. Its text part is extended from WordNet.

Distributions

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WordNet Database is distributed as a dictionary package (usually a single file) for the following software:

See also

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References

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  1. ^"WordNet News".
  2. ^"WordNet Search - 3.1".
  3. ^G. A. Miller, R. Beckwith, C. D. Fellbaum, D. Gross, K. Miller. 1990. WordNet: An online lexical database. Int. J. Lexicograph. 3, 4, pp. 235–244.
  4. ^"WordNets in the World".Global WordNet Association.Retrieved19 January2020.
  5. ^"About Global WordNet Association".Global WordNet.Retrieved19 January2020.
  6. ^"WordNet Statistics".Wordnet.princeton.edu.Retrieved2018-06-22.
  7. ^Collins A., Quillian M. R. 1972. Experiments on Semantic Memory and Language Comprehension. InCognition in Learning and Memory.Wiley, New York.
  8. ^"Integration of WordNet 1.7 in WebKB-2".Webkb.org.Retrieved2014-03-11.
  9. ^Gangemi, A.; Navigli, R.; Velardi, P. (2003).The OntoWordNet Project: Extension and Axiomatization of Conceptual Relations in WordNet(PDF).Catania, Sicily (Italy). pp. 820–838.{{cite book}}:|work=ignored (help)CS1 maint: location missing publisher (link)
  10. ^Oltramari, A.; Gangemi, A.; Guarino, N.; Masolo, C. (2002).Restructuring WordNet's Top-Level: The OntoClean approach.OntoLex'2 Workshop, Ontologies and Lexical Knowledge Bases (LREC 2002). Las Palmas, Spain. pp. 17–26.CiteSeerX10.1.1.19.6574.
  11. ^Rudnicka, Ewa; Bond, Francis; Grabowski, Łukasz; Piasecki, Maciej; Piotrowski, Tadeusz (2018). "Lexical Perspective on Wordnet to Wordnet Mapping".Proceedings of the 9th Global WordNet Conference (GWC 2018):210.
  12. ^Bond, Francis; Foster, Ryan (2013)."Linking and Extending an Open Multilingual Wordnet"(PDF).Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics:1352–1362.Retrieved20 January2020.
  13. ^Fellbaum, Christiane; Vossen, Piek (2012). "Challenges for a multilingual wordnet".Language Resources and Evaluation.46(2): 313–326.doi:10.1007/s10579-012-9186-z.S2CID10117946.
  14. ^R. Navigli.Word Sense Disambiguation: A Survey,ACM Computing Surveys,41(2), 2009, pp. 1–69
  15. ^E. Agirre, O. Lopez. 2003. Clustering WordNet Word Senses. InProc. of the Conference on Recent Advances on Natural Language (RANLP’03),Borovetz, Bulgaria, pp. 121–130.
  16. ^R. Navigli.Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance,InProc. of the 44th Annual Meeting of the Association for Computational Linguistics joint with the 21st International Conference on Computational Linguistics (COLING-ACL 2006),Sydney, Australia, July 17-21st, 2006, pp. 105–112.
  17. ^R. Snow, S. Prakash, D. Jurafsky, A. Y. Ng. 2007.Learning to Merge Word Senses,In Proc. of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL),Prague, Czech Republic, pp. 1005–1014.
  18. ^Wong, Julia Carrie(2019-09-18)."The viral selfie app ImageNet Roulette seemed fun – until it called me a racist slur".the Guardian.Retrieved2022-10-14.
  19. ^Francis Bond and Kyonghee Paik 2012a.A survey of wordnets and their licenses.In Proceedings of the 6th Global WordNet Conference (GWC 2012). Matsue. 64–71
  20. ^"Open Multilingual Wordnet".compling.hss.ntu.edu.sg.Retrieved10 April2018.
  21. ^"Ted Pedersen - WordNet::Similarity".D.umn.edu. 2008-06-16.Retrieved2014-03-11.
  22. ^NLP using Python NLTK/
  23. ^M. T. Pilehvar, D. Jurgens and R. Navigli.Align, Disambiguate and Walk: A Unified Approach for Measuring Semantic Similarity..Proc. of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Sofia, Bulgaria, August 4–9, 2013, pp. 1341-1351.
  24. ^Ballatore A, et al. (2014). "Linking geographic vocabularies through WordNet".Annals of GIS.20(2): 73–84.arXiv:1404.5372.Bibcode:2014AnGIS..20...73B.doi:10.1080/19475683.2014.904440.S2CID9246582.
  25. ^"Related projects - WordNet - Related projects".Wordnet.princeton.edu. 2014-01-06.Retrieved2018-06-22.
  26. ^The Global WordNet Association (2010-02-04)."globalwordnet.org".globalwordnet.org.Retrieved2014-03-11.
  27. ^"Wordnets in the World".Archived fromthe originalon 2011-10-21.
  28. ^Black W., Elkateb S., Rodriguez H., Alkhalifa M., Vossen P., Pease A., Bertran M., Fellbaum C., (2006) The Arabic WordNet Project, Proceedings of LREC 2006
  29. ^Lahsen Abouenour, Karim Bouzoubaa, Paolo Rosso (2013) On the evaluation and improvement of Arabic WordNet coverage and usability, Language Resources and Evaluation 47(3) pp 891–917
  30. ^D. Tufis, D. Cristea, S. Stamou. 2004.Balkanet: Aims, methods, results and perspectives. A general overview.Romanian J. Sci. Tech. Inform. (Special Issue on Balkanet),7(1-2), pp. 9–43.
  31. ^"BulNet".dcl.bas.bg.Retrieved2015-05-07.
  32. ^Chinese Wordnet ( trung văn từ hối võng lộ ) official pageat National Taiwan University
  33. ^P. Vossen, Ed. 1998. EuroWordNet: A Multilingual Database with Lexical Semantic Networks. Kluwer, Dordrecht, The Netherlands.
  34. ^"The Global WordNet Association".Globalwordnet.org. 2010-02-04.Retrieved2014-01-05.
  35. ^"FinnWordNet – The Finnish WordNet - Department of General Linguistics".Ling.helsinki.fi.Retrieved2014-01-05.
  36. ^"GermaNet".Sfs.uni-tuebingen.de.Retrieved2014-03-11.
  37. ^Pushpak Bhattacharyya, IndoWordNet, Lexical Resources Engineering Conference 2010 (LREC 2010), Malta, May, 2010.
  38. ^C. Mouton, G. de Chalendar. 2010.JAWS: Just Another WordNet Subset.InProc. of TALN 2010.
  39. ^Website
  40. ^"MCR 3.0 | Adimen".Adimen.si.ehu.es.Retrieved2022-03-21.
  41. ^E. Pianta, L. Bentivogli, C. Girardi. 2002.MultiWordNet: Developing an aligned multilingual database.InProc. of the 1st International Conference on Global WordNet,Mysore, India, pp. 21–25.
  42. ^"Open Dutch WordNet".Wordpress.let.vupr.nl. 2015-10-28.Retrieved2022-03-21.
  43. ^"arademaker/openWordnet-PT — GitHub".Github.com.Retrieved2014-01-05.
  44. ^official webpage
  45. ^official webpage
  46. ^"Русский WordNet".Pgups.ru.Retrieved2014-01-05.
  47. ^Balkova, Valentina; Sukhonogov, Andrey; Yablonsky, Sergey (2003)."Russian WordNet From UML-notation to Inter net/Intranet Database Implementation"(PDF).GWC 2004 Proceedings:31–38.Retrieved12 March2017.
  48. ^"RussNet: Главная страница".Project.phil.spbu.ru.Retrieved2014-03-11.
  49. ^"UWN: Towards a Universal Multilingual Wordnet - D5: Databases and Information Systems (Max-Planck-Institut für Informatik)".Mpi-inf.mpg.de. 2011-08-14.Retrieved2014-01-05.
  50. ^S. Benoît, F. Darja. 2008.Building a free French wordnet from multilingual resources.InProc. of Ontolex 2008,Marrakech, Maroc.
  51. ^R. Navigli, S. P. Ponzetto.BabelNet: Building a Very Large Multilingual Semantic Network.Proc. of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden, July 11–16, 2010, pp. 216–225.
  52. ^I. Niles, A. Pease 2001.Toward a Standard Upper Ontology: A large ontology for the Semantic Web and its applications.InProceedings of the 2nd International Conference on Formal Ontology in Information Systems (FOIS-2001),
  53. ^I. Niles, A. Pease 2003.Linking Lexicons and Ontologies: Mapping WordNet to the Suggested Upper Merged Ontology,InProceedings of the IEEE International Conference on Information and Knowledge Engineering,pp 412-416
  54. ^S. Reed and D. Lenat. 2002.Mapping Ontologies into Cyc.InProc. of AAAI 2002 Conference Workshop on Ontologies For The Semantic Web,Edmonton, Canada, 2002
  55. ^Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltramari, A., Schneider, L.S. 2002.WonderWeb Deliverable D17. The WonderWeb Library of Foundational Ontologies and the DOLCE ontology.Report (ver. 2.0, 15-08-2002)
  56. ^Gangemi, A., Guarino, N., Masolo, C., Oltramari, A. 2003Sweetening WordNet with DOLCE.In AI Magazine 24(3): Fall 2003, pp. 13–24
  57. ^C. Bizer, J. Lehmann, G. Kobilarov, S. Auer, C. Becker, R. Cyganiak, S. Hellmann,DBpedia – A crystallization point for the Web of Data.Web Semantics, 7(3), 2009, pp. 154–165
  58. ^S. M. Harabagiu, G. A. Miller, D. I. Moldovan. 1999.WordNet 2 – A Morphologically and Semantically Enhanced Resource.InProc. of the ACL SIGLEX Workshop: Standardizing Lexical Resources,pp. 1–8.
  59. ^J. Deng, W. Dong, R. Socher, L. Li, K. Li, L. Fei-Fei.ImageNet: A Large-Scale Hierarchical Image Database.InProc. of 2009 IEEE Conference on Computer Vision and Pattern Recognition
  60. ^M. Poprat, E. Beisswanger, U. Hahn. 2008.Building a BIOWORDNET by Using WORDNET’s Data Formats and WORDNET’s Software Infrastructure – A Failure Story.InProc. of the Software Engineering, Testing, and Quality Assurance for Natural Language Processing Workshop,pp. 31–39.
  61. ^S. Ponzetto, R. Navigli.Large-Scale Taxonomy Mapping for Restructuring and Integrating Wikipedia,InProc. of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009),Pasadena, California, July 14-17th, 2009, pp. 2083–2088.
  62. ^S. P. Ponzetto, R. Navigli.Knowledge-rich Word Sense Disambiguation rivaling supervised systems.In Proc. of the 48th Annual Meeting of the Association for Computational Linguistics (ACL), 2010, pp. 1522–1531.
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