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Boeing’s Language Understanding Engine (BLUE) A Quick Tutorial

Boeing’s Language Understanding Engine (BLUE) A Quick Tutorial. Peter Clark Phil Harrison (Boeing Phantom Works). What is a Semantic Representation?. “Leftist”. “Rightist”. Semantic structure close to syntactic structure , need more downstream interpretation. Semantics more explicit.

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Boeing’s Language Understanding Engine (BLUE) A Quick Tutorial

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  1. Boeing’s Language Understanding Engine (BLUE)A Quick Tutorial Peter Clark Phil Harrison (Boeing Phantom Works)

  2. What is a Semantic Representation? “Leftist” “Rightist” Semantic structure close to syntactic structure, need more downstream interpretation Semantics more explicit. causes(virus01,c-cancer01) forall c isa(c,c-cancer) → exists e,v isa(e,event), isa(v,virus), involves(e,v), causes(e,c) (2.1) "Cervical cancer is caused by a virus." forall c isa(c,c-cancer) → exists v isa(v,virus), causes(v,c)

  3. Semantic Formalism • Ground (Skolemized) first-order logic assertions • No quantification (left for downstream processing) “An object is thrown from a cliff.” isa(object01,object_n1), isa(cliff01,cliff_n1), isa(throw01,throw_v1), object(throw01,object01), origin(throw01,cliff01). • Embedding used for modals (6.3) "The farm hopes to make a profit" isa(farm, farm_n1), ….. agent(hope01,farm01), object(hope01,[ agent(make02,farm01), object(make02,profit02)])

  4. BLUE’s Pipeline Throw object origin Object Cliff “An object is thrown from a cliff” Parser & LF Generator Initial Logic Generator Word Sense Disambiguation Semantic Role Labeling Coreference Resolution Metonymy Resolution Structural Reorganization Linguistic and World Knowledge isa(object01,object_n1), isa(cliff01,cliff_n1), isa(throw01,throw_v1), object(throw01,object01), origin(throw01,cliff01).

  5. 1. Parsing/Logical Form Generation • Parsing: SAPIR, a bottom-up chart parser, guided by • Hand-coded cost function • “tuples” – examples of attachment preferences (VPN "fall" "onto" "floor") (VPN "flow" "into" "body") (NN "lead" "iodide") (NPN "force" "on" "block") (NPN "speed" "at" "point") (NPN "chromosome" "in" "cell") (NPN "force" "during" *) (NPN "distance" "from" *) (NPN "distance" "to" *) • Several 100 authored by hand • 53 million generated automatically • Logical Form: Classical compositional rule-based approach

  6. 2. Initial logic generation isa(object01,object_n1), isa(cliff01,cliff_n1), isa(throw01,throw_v1), object(throw01,object01), origin(throw01,cliff01). Final Logic “An object is thrown from a cliff” (DECL ((VAR _X1 "an" "object") (VAR _X2 "a" "cliff")) (S (PRESENT) NIL "throw" _X1 (PP "from" _X2)) Logical form "object"(object01), "cliff"(cliff01), "throw"(throw01), sobject(throw01,object01), "from"(throw01,cliff01). Initial Logic

  7. 3. Subsequent Processing • Word Sense Disambiguation: • Naïve use of WordNet (70% ok) • For applications using CLib ontology, then do a mapping: CLib Ontology WordNet Physical-Object “object” Goal Concept (Word Sense) Lexical Term

  8. 3. Subsequent Processing Throw Throw sobject object “from” origin Object Object Cliff Cliff • Semantic Role Labeling: • ~40 semantic roles (from Univ Texas) • Assign using a hand-built database of (~100) rules IF X “of” Y and X is Physical-Object and Y is Material THEN X material Y • Moderate performance

  9. 3. Subsequent Processing • Coreference • Same name = same object • Same/subsuming noun phrase = same object • “The red block fell. The block that had fallen was damaged.” • Ordinal reference • “A block is on a block. The second block is larger.” • Metonymy resolution • Mainly with CLib KB “H2O reacts with NaCl” React React raw-material raw-material raw-material raw-material Chemical Chemical H2O NaCl basic-unit basic-unit H2O NaCl

  10. 3. Subsequent Processing • Structural Reorganization property Cliff Height “the height of the cliff” height Cliff Value Contain subject object “the box contains a block” Box Block content Box Block property kg 10 “10 kg” value Weight-Value (:pair 10 kg)

  11. 3. Subsequent Processing • Structural Reorganization “be” and “have” Be subject object (a) equality color Block Color Red “the color of the block is red” color Block Red (b) other relation Be subject object “the block is red” Block Red color Block Red

  12. Summary BLUE: • Formalism: • Skolemized first-order logic predicates • Embedding for modals • Mechanism: • Parser → LF generator → initial logic → post-processing • Performance: • Many sentences are mostly right  • Most sentences have something wrong 

  13. Thank you!

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