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Interactively Discovering Implicational Knowledge in Wikidata

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Video duration
00:31:11
Language
English
Abstract
The ever-growing Wikidata contains a vast amount of factual knowledge. More complex knowledge, however, lies hidden beneath the surface: it can only be discovered by combining the factual statements of multiple items. Some of this knowledge may not even be stated explicitly, but rather hold simply by virtue of having no counterexamples present on Wikidata. Such implicit knowledge is not readily discoverable by humans, as the sheer size of Wikidata makes it impossible to verify the absence of counterexamples. We set out to identify a form of implicit knowledge that is succinctly representable, yet still comprehensible to humans: implications between properties of some set of items. Using techniques from Formal Concept Analysis, we show how to compute such implications, which can then be used to enhance the quality of Wikidata itself: absence of an expected rule points to counterexamples in the data set; unexpected rules indicate incomplete data. We propose an interactive exploration process that guides editors to identify false counterexamples and provide missing data. This procedure forms the basis of [The Exploration Game](https://tools.wmflabs.org/teg/), a game in which players can explore the implicational knowledge of set of Wikidata items of their choosing. We hope that the discovered knowledge may be useful not only for the insights gained, but also as a basis from which to create entity schemata.

The talk will introduce the notions of Implicational Knowledge, describe how Formal Context Analysis may be employed to extract implications, and showcase the interactive exploration process.

Talk ID
36c3WPWG-95
Event:
36c3-wikipaka
Day
2
Room
WikiPaka WG: Esszimmer
Start
4 p.m.
Duration
00:30:00
Track
Science
Type of
Talk
Speaker
Maximilian Marx
Tom Hanika
Talk Slug & media link
36c3-95-interactively-discovering-implicational-knowledge-in-wikidata

Talk & Speaker speed statistics

Very rough underestimation:
153.7 wpm
846.8 spm
While speaker(s) speak(s):
161.0 wpm
884.7 spm
151.4 wpm
849.2 spm
173.1 wpm
929.1 spm
100.0% Checking done100.0%
0.0% Syncing done0.0%
0.0% Transcribing done0.0%
0.0% Nothing done yet0.0%
  

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Talk & Speaker speed statistics with word clouds

Whole talk:
153.7 wpm
846.8 spm
wikidatanobelpropertiestrueprizeknowledgedatapropertyexamplecounterexamplesmissingimplicationquestioncardexpertcounterexampleformalphysicsimplicationsfindcontextworkbasicallygamepeopletoolitemscalledstricklandalgorithmwrongentitiesfeemouroutomfieldcaseapplausethingawardedquestionsstatementsmaxnetworktablelasersoperatorentitychemistryeasy
While speakers speak:
161.0 wpm
884.7 spm
wikidatanobelprizetruepropertiesknowledgepropertycounterexamplesformaldataexpertcardexamplephysicsworkimplicationcontextmissingimplicationsstricklandalgorithmgamebasicallyitemspeoplecalledmouroufeestatementsawardedfieldlasersfindtablecounterexamplecasenetworkoperatorentityentitiesdonnareceivedcuriechemistryeasyrulesimplicitanalysissetmammal
Maximilian Marx:
151.4 wpm
849.2 spm
nobelprizewikidatapropertiesknowledgephysicsworkpropertystricklandmourouimplicationsmissingformalcontextawardedfieldlasersstatementscounterexamplesawardbasicallypeoplecuriechemistrydonnareceivedcurrentlyformimplicationentityreceivingwinningyeargérardqualifierentitiesradioactivitymarieitemscomingtomtableincidenceactualstatementcalledchild2018ashkinarnold
Tom Hanika:
173.1 wpm
929.1 spm
wikidatatruedatacardexpertexamplealgorithmknowledgefeegamecasepropertiesnetworkoperatorimplicationcounterexamplesvalidcounterexampleformalmammaleggsrulesleftcalledexplorationrejectfindquestionproperty26itemseasycontextvenomousrulehumanimplicittoolstatecreditexplorenumbermissingsetawareimplicationsanalysislatticesteaksobjects