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Discussion of open issues. Cases of meaning equivalence. Creative Language use Metaphorical language Al7ayah ba2a lwnha bamby 5ales [Egyptian Arabic BOLT data] [gloss] the-life became colored pink extremely [Trans1] Life is so pink [Trans2] Everything is extremely hunky dory
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Cases of meaning equivalence • Creative Language use • Metaphorical language • Al7ayah ba2a lwnhabamby 5ales [Egyptian Arabic BOLT data] • [gloss] the-life became colored pink extremely • [Trans1] Life is so pink • [Trans2] Everything is extremely hunky dory • [Trans3] Life is quite rosy • Sarcasm • Great, now I have to be at work at 5am • Great, now I have to be at work at 10am • Etc. • Pronominal Usage • He ate the apple • She ate the apple • The notion of salience and the role it plays with respect to context (the IBM example, Sameer’s presentation)
Current Tools and Resources • Current semantic technologies • WSD, WSI, Lexical substitution, SRL, modality, distributional compositionality, MWE, scoping, conversion from surface form to logical structure • Current resources • WN, ontologies (SUMO), MRD, ontonotes, UVI, verbnet, propbank, framenet
What other things are needed? • Tools • Creative language use detectors (work by Veale, Muresan, also some by us here on sarcasm) • Metaphor, irony, sarcasm • Register/style/salience detectors • Resources • Generalizable predicate relations detectors (extend the UVI to be more comprehensive) • Annotations for pragmatic stuff • What data do we annotate? (Multi)MASC
What platform to adopt? • Should we go with something like UIMA, or with Nancy’s grant • We can probably start with UIMA and then transfer over especially if we want webservices and cloud computing capabilities
What semantic interoperability standards do we adopt? • CAS • OWL • KAF • Etc.
Precursor issues • Refine STS definition • Create an inventory of possible relations we observe between two textual snippets • Devise set of diagnostics for each of these relations in the inventory • Equivalence (substitutability) • Entailment • Contradiction • Specificity • Subset • etc • What role does the Topic/domain play • What role does the context play • What role does the native language/culture play
Refine the STS Annotation Framework • Adopt and work on Diana, Alessandro Lenci, Ido, Bernardo, Alon’s insights on how to modularize and concretize the task of STS for humans • Three types of annotations • Cast as an alignment + scores • Decouple alignment from overall scores • Just scores • How do we obtain the annotations • Turkers? • Trained people?
Evaluation Issues • Intrinisicvs Extrinsic measures • What is desirable • How does it correlate with application needs
Next steps • Balancing act of functionality/utility/ontological issues • Create this community • Committees to work on the different aspects • Shared Task • *SEM as a venue • Use Nancy’s challenge idea • Seek funding from different resources • NSF • DARPA • AirForce • IARPA • Potential for European/Asian collaboration