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NLP2RDF Wortschatz and Linguistic LOD draft
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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
2.
3.
4.
5.
Text
6.
7.
8.
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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