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Danica Damljanović, Milan Agatonović, Hamish Cunningham contact: FREyA: an Interactive Way of Querying Linked Data using Natural.

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Presentation on theme: "Danica Damljanović, Milan Agatonović, Hamish Cunningham contact: FREyA: an Interactive Way of Querying Linked Data using Natural."— Presentation transcript:

1 Danica Damljanović, Milan Agatonović, Hamish Cunningham contact: FREyA: an Interactive Way of Querying Linked Data using Natural Language

2 N ATURAL L ANGUAGE I NTERFACES AND L INKED O PEN D ATA  What are NLIs?  Challenges:  NL understanding/grammar  ambiguity/expressiveness  knowledge structure/portability small ontologies, large ontologies, multiple ontologies, Linked Open Data? 30 MAY 2011 QALD-1 2

3 S HIFT IN C HALLENGES 30 MAY 2011 QALD-1 3 Closed-domainOpen-domain Find the answerDisambiguate the answer Language ambiguityData ambiguity Increase recall (Wordnet, etc.)Increase precision  Portability 5 years ago vs. today?  Heterogeneity, incompleteness, redundancy  Can one system support both?

4 FRE Y A WORKFLOW 30 MAY 2011 QALD-1 4

5 F INDING POC S 03 J UNE 2010 ESWC

6 F INDING OC S 03 J UNE 2010 ESWC

7 geo:City geo:State new york POC population geo:cityPopulation M APPING POC TO OC S 03 J UNE 2010 ESWC geo:State

8 N EW Y ORK IS A CITY 03 J UNE 2010 ESWC

9 N EW Y ORK IS A STATE 03 J UNE 2010 ESWC

10 L EARNING 10 POCOC (context)candidate OCfunction new yorkgeo:State- new yorkgeo:City- populationgeo:Stategeo:statePopulation- populationgeo:Citygeo:cityPopulation- IFTHEN

11 L EARNING 11

12 Q UERYING L INKED D ATA WITH FRE Y A: THE USUAL CYCLE 30 MAY 2011 QALD-1 12 for i=1 to n { Initialise the system using dataset A i (forceDialog) Train the system by asking questions Save learningModel i } Intialise the system (automatic mode) by loading learningModel i, i=1,n connect to the repository containing all A i datasets, where i=1, n

13 EVALUATION  Initialisation  System performance  Precision, recall, f-measure using MusicBrainz and DBPedia datasets  Mean Reciprocal Rank to assess the effect of learning mechanism  Analysis of failures 30 MAY 2011 QALD-1 13

14 I NITIALISATION AND THE DATASETS SIZE MusicBrainzDBpedia explicit statements statements entities SPARQL queries initialisation time1380s (0.38h)182779s (50.77h) 30 MAY 2011 QALD-1 14

15 R ESULTS : F- MEASURE STATISTICS MusicBrainzDBPedia Training Testing Precision0.75/ / / /0.63 Recall0.66/ / / /0.54 F-measure0.70/ / / /0.58 not supported questions reformulated questions avg #dialogs per question partially correct questions MAY 2011 QALD-1 15

16 L EARNING MusicBrainzDBPedia untrained/trained MRR0.63/ / MAY 2011 QALD-1 16

17 C ONCLUSION  Output:  Correct answer OR  Identifying the flaws in the data?  Ranking/disambiguation algorithms to improve MRR 30 MAY 2011 QALD-1 17 Closed-domainOpen-domain End-usersApplication developer

18 Contact: THANK YOU FOR YOUR ATTENTION ! QUESTIONS ? 18 Thanks to Ivan Peikov from Ontotext who helped with the configuration of OWLIM which was necessary for performing the experiments reported in this paper.

19 D EMO United States geography: ml MusicBrainz: tml DBpedia: ya.html


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