Multilingual Extraction Ontologies. Outline Our MEG A possible WWW paper Getting there from here What we propose(d) to do Multilingual resources Evaluation.

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Presentation transcript:

Multilingual Extraction Ontologies

Outline Our MEG A possible WWW paper Getting there from here What we propose(d) to do Multilingual resources Evaluation

MEG details Funding Starts ASAP Stops at end 2011 PI’s: Embley, Liddle, Lonsdale, Tijerino $20,000 total: $18,000 for student wages, $1500 for travel, $500 for supplies (mobile device)

MEG objective(s) 1.Enhance ontologies: Compound recognizers Pattern discovery Discover and extract relationships among objects Discover patterns that can lead to identification and extraction of object instances and relationship instances

MEG objective(s) 2.Demonstrate crosslinguistic viability of ontologies Create crosslinguistic mappings Integrate lexicons for multilingual processing Develop multilingual (crosslingual?) value recognizers

MEG objective(s) 3.Tech transfer Develop working prototype showing multilingual capabilities Hand-held travel assistant Build business plan, enter BYU competition Develop patent application

Research plan Winter 2010: recruit students CS undergrad Linguistics undergrad e-business undergrad Activities Setup: Eclipse, OntoES, repository

Premises English Web is increasingly being overshadowed We want to show viability of our approach crosslinguistically Some efforts exist: Norwegian drilling, VerbMobil, EU trains, CLEF, NTCIR Not all use ontologies

Approach Declare a narrow domain ontology (cf. car ads) Add linguistic recognizers (data frames ++) Extend to (an)other language(s) Let ontological content be a sort of “interlingua”

Japanese extraction ontology

Multilingual adaptation OntoES, workbench should be inherently capable UTF-8, Java Some work remains Knowledge sources Many exist; don’t have resources to re- invent the wheel WordNet, termbases

CS-related work New algorithms, data structures for linguistically-grounded intologies Implement compound recognizers Design and run evaluation

Linguistics-related work Locate and evaluate lexical resources Engineer ways to implement multiple or crosslinguistic language resources Help in system evaluation

Business-related work Research needs of international travelers Brainstorm business app, do market research Write, submit business plan Investigate tech transfer, patent issues