NLP2RDF Wortschatz and Linguistic LOD draft

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Sebastian Hellmann

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Extensive Topic – Whatisthecore? Features forMachine Learning Whichfeatures do I needfor a certain Textmining task? An introductoryexample : Resources: ,[object Object]

Database withAgeandOccupationGoal: predictincomeofpersons ,[object Object],=> Color ofeyesandhaircutprobably irrelevant!

Basic idea: a benchmarkingframework Input: ,[object Object]

Training/testdataOutput: ,[object Object],Do I need POS tags toclassifyTourismdocuments? Prerequisites: ,[object Object]

Data needs a standardizedformat,[object Object]

Basic idea: a benchmarkingframework Google Code project was created ,[object Object]

SomeresultswereachievedBut… ,[object Object]

Speed ofintegrationtooslow,[object Object]

Why RDF and OWL ? RDF makesdataintegration easy: URIref, LinkedData OWL isbased on Description Logics (Guarded Fragment) Availabilityof open datasets (accessandlicence) Diverse serializationsforannotations: XML, Turtle, RDFa+XHTML Scalabletoolsupport (Databases, Reasoning) 6. Iftheonlytoolyouhaveis a hammer, everythinglookslike a nail.

LOD Cloud - over 26 Billion Facts DBpediaiscentral: ,[object Object]

Crystalizationpoint (earlybird)Linking Open Data clouddiagram, by Richard CyganiakandAnja Jentzsch. http://lod-cloud.net/

Links areHTTP-Foreign Keys,[object Object]

URIs pointingtosubjects in the same table

URIs pointingtosubjects in anyothertable,[object Object]

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NLP2RDF Wortschatz and Linguistic LOD draft

1. NLP2RDFIntegration of Data, Tools andApplicationswith RDF/OWL in the Areas of Textmining andLinguistics PhD Thesis, Sebastian Hellmann

5. Text

9. Ontologieswerefoundandintegrated

10. Pipeline implemented

11. Pluginsystemimplemented

12.

13. Integration boundto Java

14. Data sourceswere not sufficient

15. Wikipedia/DBpediatoocourse-grained

16.

17. Why RDF and OWL ? RDF makesdataintegration easy: URIref, LinkedData OWL isbased on Description Logics (Guarded Fragment) Availabilityof open datasets (accessandlicence) Diverse serializationsforannotations: XML, Turtle, RDFa+XHTML Scalabletoolsupport (Databases, Reasoning) 6. Iftheonlytoolyouhaveis a hammer, everythinglookslike a nail.

18.

19. Crystalizationpoint (earlybird)Linking Open Data clouddiagram, by Richard CyganiakandAnja Jentzsch. http://lod-cloud.net/

20.

21.

22. URIs pointingtosubjects in the same table

23.

24. SPARQL – optimizationsfortablejoins

25. Creationofdatasets: Wiktionary2RDF

26.

27. Total of 10 millionpages

28. 900.000 users

29. RDF Dump will increasenumberofeditors

30. Same propertiesas Wikipedia (stableidentifiers)

31. HundredsofWiktionaryparsers (especiallyfor English)

32. Information istrapped in theWiki

33.

34. Configurationover Code, Templates will allowWiktionariansto update Parsers

35.

36. Usecases

37. Other datasetsto link to!

38. Wikipedia as a linkingpartner not suited

39.

40. Dictionaries

41. Corporas

42.

43. WhichWiktionaryrelationcanbelinkedtowhichstatisticalrelation?

44. Can webuildtoolsthathelpsWiktionaryeditors (Suggestions)?

45. Wiktionary links Words acrosslanguages. Are thereanysimilarpatterns?

46.

47. 6-7 Members

48.

49.

50. Relation betweenStrings: previous, next, sub, super

51.

52. Multiple servicescanbe ad-hoc integrated

53. Multiple layersofannotationcanbeused

54. Fullcompatabilitywith POWLA

55.

56. Ontology Learning Johanna Völker – Learning Expressive Ontologies(LExO) # Example: # A fishisanyaquaticvertebrateanimalthatiscoveredwithscales, # andequippedwithtwosetsofpairedfinsandseveralunpairedfins. # # [fish] subClassOf [anyaquaticvertebrateanimalthatiscovered…] #Construct {?subrdfs:subClassOf ?super} { Construct {?subowl:equivalentClass ?super} { ?is a penn:BePresentTense . ?isnlp:superToken ?is_any_aquatic_. ?is_any_aquatic_ a olia:VerbPhrase . ?is_any_aquatic_ nlp:syntacticSubToken [ nlp:normUri ?super] . ?animalnlp:cop ?is . ?animalnlp:nsubj ?fish .?fishnlp:superToken [ nlp:normUri ?sub] . }

57. Standing on theshouldersofgiants Christian Chiarcos SFB632 - Uni Potsdam Johanna Völker Uni Mannheim Markus Strohmaier, TU Graz Thankyouforyourattention Jens Lehmann Uni Leipzig Sören Auer Uni Leipzig

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