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A Two-way Bridge between Language and Logic Recent Accomplishments and Challenges

A Two-way Bridge between Language and Logic Recent Accomplishments and Challenges. Danny Bobrow and Ron Kaplan With Cleo Condoravdi, Dick Crouch, Valeria de Paiva, Lauri Karttunen, Tracy King, John Maxwell, Annie Zaenen. XLE/LFG Parsing. Target Logic. KR Mapping. Text. F-S. C-S. KR.

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A Two-way Bridge between Language and Logic Recent Accomplishments and Challenges

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  1. A Two-way Bridge between Language and LogicRecent Accomplishments and Challenges Danny Bobrow and Ron Kaplan With Cleo Condoravdi, Dick Crouch, Valeria de Paiva, Lauri Karttunen, Tracy King, John Maxwell, Annie Zaenen AQUAINT: Two-Way Bridge

  2. XLE/LFG Parsing Target Logic KR Mapping Text F-S C-S KR Sources Assertions M M Question Query Answers Explanations Subqueries Composed F-Structure Templates Text to user XLE/LFG Generation Text M Outline • Recent accomplishments • Some technical details • Collaborative challenges AQUAINT: Two-Way Bridge

  3. Accomplishments:Incorporation of external resources • Cyc extractions • Generalization hierarchy • Language to KR mappings • VerbNet extractions • Syntactic lexicon, subcategorization frames • Thematic roles and semantics • Linkage between syntax and semantics AQUAINT: Two-Way Bridge

  4. Accomplishments:Test suites • XLE syntactic coverage with gold standards • Extracted examples: WordNet, VerbNet, NIST • PropBank mapping to full sentence, dependency triples (including stemmed verbs & argument heads) • Project specific • Key phenomena context inducing constructions, questions, time expressions, etc • Domains terrorism (bombings and money laundering), travel, commercial transactions AQUAINT: Two-Way Bridge

  5. Accomplishments:System Work • PARC advances • Semantics-KR mapping in term-rewriting system • XLE, Glue, term-rewriting in one process • Uniform use of XLE packed ambiguity management • Exploration and exploitation • ResearchCyc • ANSProlog • WordNet AQUAINT: Two-Way Bridge

  6. Morphology PARC Architecture Word structure Entity recognition Text XLE/LFGparsing C-structure LFG GrammarLexicon F-structure Gluederivation Semanticlexicon Linguisticsemantics VerbNetWordNet TermRewriting Conceptual & Contexted KR (Bridge KR) Mapping Rules Cyc TargetKRR Cyc ANSProlog AQUAINT: Two-Way Bridge

  7. Layered Mapping from F-Structures to KR Natural decomposition through intermediate representations with different formal characteristics that capture different generalizations • Glue derivation: F-structure to linguistic semantics • Captures intensionality, scope variation, etc • Shows logical structure by nesting of formulas • Linguistic semantics to flattened clausal form • Use skolems as terms to encode structure • Bridges between linguistic structure and knowledge structure • Map semantic clauses to Bridge KR clauses • Use resourced term-rewriting with ambiguity management • Canonicalizes to more uniform (easier to match) representations • Map from Bridge KR to target KR AQUAINT: Two-Way Bridge

  8. Glue DerivationF-Structure to Linguistic Semantics • Two parallel, linked logics • Resourced linear logic for guiding semantic construction • Derivation driven solely by F-structures as types • A meaning logic for semantic representation • Composition driven by linear logic derivation • Alternative derivations introduce semantic ambiguities • Quantifier scope ambiguity • Every cable is attached to a base-plate • x cable(x)  y plate(y) & attached(x,y) • y plate(y) & x cable(x)  attached(x,y) • Internal/external modification • John put up bookshelves for two days • Working on it for two days, or stayed up for two days • Comparison sets in information structure • Pets must be carried on escalator • Clothes must be worn in public AQUAINT: Two-Way Bridge

  9. Flat, packed semantics ist(c0, terrorist(t)) ist(c0, cardinality(t, 2)) ist(c0, plan(t, c1)) ist(c1, attack(a, t, f)) skfn(t, c0) skfn(c1, t) skfn(a, c1) A1: ist(c0, factory(f)) B1: skfn(f,c0) B2: skfn(f, t) A2: skfn(f, c1) A2: ist(c1, factory(f)) c0 is the top level context c1 is the context of the plan ist(C,X): X is true in context Cskfn(sk, arg): skolem sk depends on arg Linguistic semantics and flattened clauses Result of glue derivation Two terrorists plan to attack a factory A1,B1: exists(f. factory(f) & exists2(t. terrorist(t) & plan(t, exists(a. attack(a, t ,f)))) One real factory for both terrorists A1,B2: exists2(t. terrorist(t) & exists(f. factory(f) & plan(t, exists(a. attack(a, t ,f))))) A different real factory for each terrorist A2: exists2(t. terrorist(t) & plan(t, exists(f. factory(f) & exists(a. attack(a, t, f))))) The terrorists haven’t chosen factories AQUAINT: Two-Way Bridge

  10. Skolems refer to subconcepts • terrorist(t) • t does not refer to an individual that is a terrorist • rather t refers to a subconcept of the concept “terrorist” • Permits a simpler treatment of intensional constructions • Negotiations prevented a war • n. subconcept(n, Negotiation) & w. subconcept(w, War) & prevent(n,w) • prevent(n,w) means that • concept n has instances (in the world of the prevention) • concept w has no instances in that world AQUAINT: Two-Way Bridge

  11. After Glue and Flattening:Mapping to Bridge KR • Map to concepts & roles in ontology (Cyc) • Apply meaning postulates / lexical entailments • Make conceptual & contextual structure explicit • Eliminate ontologically ill-formed analyses AQUAINT: Two-Way Bridge

  12. Example Abstract KR (I)Words  Cyc Terms & Roles • Ed got to Baghdad (objectMoving get_ev5 Ed7) (toLocation get_ev5 Baghdad6) (sub_concept get_ev5 Conveying-Generic) (sub_concept Baghdad6 CityOfBaghdadIraq) (sub_concept Ed7 Ed-default-name) (instantiated t Ed7) (instantiated t Baghdad6) (instantiated t get_ev5) • Ed got the package to Baghdad (objectMoving get_ev8 package9) (toLocation get_ev8 Baghdad10) (doneBy get_ev8 Ed11) … • Ed got the package (objectMoving get_ev12 package14) (toLocation get_ev12 Ed13) … AQUAINT: Two-Way Bridge

  13. Example Abstract KR (II)Canonicalization • Ed cooled the room (sub_concept cool_ev18 scalar-state-change) (decreasesCausally cool_ev18 room20 temperatureOfObject) (doneBy cool_ev18 Ed21) (sub_concept room20 RoomInAConstruction) … • Ed lowered the temperature of the room (sub_concept lower_ev22 scalar-state-change) (decreasesCausally lower_ev22 room24 temperatureOfObject) (doneBy lower_ev22 Ed23) (sub_concept room24 RoomInAConstruction) … • The room cooled (sub_concept cool_ev25 scalar-state-change) (decreasesCausally cool_ev25 room26 temperatureOfObject)) (sub_concept room26 RoomInAConstruction) … AQUAINT: Two-Way Bridge

  14. Example Abstract KR (III)Contextual Structure • The senator prevented a war preventRelation (action1 c0 c2) doneBy (action1 senator3) sub_concept (action1 Eventuality) sub_concept (senator3 USSenator) sub_concept (war4 WagingWar) instantiated (c0 senator3) instantiated (c0 action1) uninstantiated (c0 war2) uninstantiated (c2 action1) instantiated (c2 war2) AQUAINT: Two-Way Bridge

  15. Term-Rewriting for KR Mapping • Rules of form • <Input terms> ==> <Output terms> (obligatory) • <Input terms> ?=> <Output terms> (optional) (optional rules introduces new choices) • Input patterns allow • Consume term if matched: Term • Test on term without consumption: +Term • Test that term is missing: -Term • Procedural attachment: {ProcedureCall} hire(E), subj(E, X), obj(E, Y), +sub_concept(X, CX), +sub_concept(Y, CY),{genls(CX, Organization), genls(CY, Person)} ==> sub_concept(E, EmployingEvent), performedBy(E,X), personEmployed(E,Y). • Ordered rule application • Rule1 applied in all possible ways to Input to produce Output1 • Rule2 applied in all possible ways to Output1 to produce Output2 Example Rule AQUAINT: Two-Way Bridge

  16. Term-rewriting can introduce ambiguity Permanent Background Facts • Alternative lexical mappings /- cyc_concept_map(bank, FinancialInstitution)./- cyc_concept_map(bank, SideOfRiver). ist(C, P(Arg)), cyc_concept_map(P,Concept) ==> sub_concept(Arg,Concept). • Input term • ist(c0, bank(b1)) • Alternative rule applications produce different outputsRewrite system represents this ambiguity by a new choice • Output • C1: sub_concept(b1, FinancialInstitution)C2: sub_concept(b1, SideOfRiver) • (C1 xor C2)  1 Mapping from Predicate to Cyc concept AQUAINT: Two-Way Bridge

  17. Term-rewriting can prune ill-formed mappings • The bank hired Ed hire(E), subj(E,X), obj(E,Y), +sub_concept(X,CX), +sub_concept(Y,CY),{genls(CX, Organization), genls(CY,Person)} ==> sub_concept(E, EmployingEvent), performedBy(E,X), personEmployed(E,Y). • From Cyc: genls(FinancialInstitution, Organization) true genls(SideOfRiver, Organization) false • If bank is mapped to SideOfRiver, the rule will not fire.This leads to a failure to consume the subject. subj(A,B) ==> stop. prunes this analysis from the choice space. • In general, later rewrites prune analyses that don’t consume grammatical roles. Rule for mapping hire AQUAINT: Two-Way Bridge

  18. Mapping to Target KR: Collaborative Challenges • Target ontology • Cyc – extending the ontology • ANSProlog -- mapping from Cyc ontology • Packed ambiguity • Pass on packed ambiguities? • Unpack possible interpretations? • Choose statistically most likely? • Contexts • Cyc: will microtheories work? • ANSProlog: incorporating a logic of contexts? AQUAINT: Two-Way Bridge

  19. Two forms of future evaluation • Project • Regression test suites to ensure progress towards benchmark representations • Matching algorithm to test utility of KR canonicalization • AQUAINT Program: • Local textual inference? • Incorporation by a back-end system? AQUAINT: Two-Way Bridge

  20. Thank you AQUAINT: Two-Way Bridge

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