When life gives you lemons, make GF! Inducing grammars from the - PowerPoint PPT Presentation

When life gives you lemons, make GF! Inducing grammars from the lexicon-ontology interface Christina Unger Semantic Computing Group CITEC, Bielefeld University 1 / 41

In collaboration with: Jeroen van Grondelle, Frank Smit, Jouri Fledderman (Be Informed, The Netherlands) 2 / 41

Motivation Conceptually scoped language technology 3 / 41

Today Natural language plays an increasingly important role as interface to existing services and data. 4 / 41

1 Alignment of natural language expressions and . domain concepts, data or services Would I get housing benefits? ASK WHERE :user :eligible "true". 2 High precision (reliability and predictability) . . 3 Expertise and time for creating and maintaining . . grammars (and for porting it across languages or switching domains) 4 Unrestricted coverage . . Requirements 5 / 41

2 High precision (reliability and predictability) . . 3 Expertise and time for creating and maintaining . . grammars (and for porting it across languages or switching domains) 4 Unrestricted coverage . . Requirements 1 Alignment of natural language expressions and . . domain concepts, data or services Would I get housing benefits? ASK WHERE { :user :eligible "true". } 5 / 41

3 Expertise and time for creating and maintaining . grammars (and for porting it across languages or switching domains) 4 Unrestricted coverage . . Requirements 1 Alignment of natural language expressions and . . domain concepts, data or services Would I get housing benefits? ASK WHERE { :user :eligible "true". } 2 High precision (reliability and predictability) . . 5 / 41

4 Unrestricted coverage . . Requirements 1 Alignment of natural language expressions and . . domain concepts, data or services Would I get housing benefits? ASK WHERE { :user :eligible "true". } 2 High precision (reliability and predictability) . . 3 Expertise and time for creating and maintaining . . grammars (and for porting it across languages or switching domains) 5 / 41

Requirements 1 Alignment of natural language expressions and . . domain concepts, data or services Would I get housing benefits? ASK WHERE { :user :eligible "true". } 2 High precision (reliability and predictability) . . 3 Expertise and time for creating and maintaining . . grammars (and for porting it across languages or switching domains) 4 Unrestricted coverage . . 5 / 41

Conceptually scoped language technology The underlying application introduces a conceptual scope that determines the language fragment that is relevant and meaningful. 6 / 41

Goal CONCEPTUALIZATION LEXICAL INFORMATION GRAMMAR (ONTOLOGY) (ONTOLOGY LEXICON) . . 7 / 41

If life gives you lemons... The lexicon-ontology interface 8 / 41

Ontology Example: Fresh water animals predator conservationStatus . . . . . . . . . . . . . . . . . . Species String pollution livesIn BodyOfWater Integer Bird Fish in Heron Crayfish Country Sea Raven Perlfish 9 / 41

Modelling data w.r.t. an ontology Example: Chiemsee fish 1 :Germany rdf:type :Country . 2 :Chiemsee rdf:type :BodyOfWater ; :in :Germany ; 3 :pollution 2 . 4 5 6 :ChiemseeCrayfish rdf:type :Crayfish ; :livesIn :Chiemsee ; 7 :conservationStatus "EX" . 8 9 10 :ChiemseePerlfish rdf:type :Perlfish ; :livesIn :Chiemsee ; 11 :predator :Heron, :SeaRaven ; 12 :conservationStatus "EN" . 13 10 / 41

Ontology lexica Aim: capture rich and structured linguistic information about how ontology elements are lexicalized in a particular language 11 / 41

Why simple terminological knowledge is not enough The conceptual granularity of language often does not coincide with that of the schema underlying a particular dataset... :team → to play for if the subject is any kind of player → to race for if the subject is a race driver ...and can also vary across languages. :eat → en eat → de essen if the subject is a human → de fressen if the subject is an animal 12 / 41

Why simple terminological knowledge is not enough Not only lexicalizations of single classes or properties are relevant, but also lexicalizations of complex constructions. � Which fish live in Germany? livesIn in . . . . . . BodyOfWater Country Fish � Which fish are endangered? conservationStatus . . . . Species "EN" 13 / 41

lemon (Lexicon Model for Ontologies) http://lemon-model.net � meta-model for describing ontology lexica with RDF � declarative, thus abstracting from specific syntactic and semantic theories � separation of lexicon and ontology . Semantics by reference . The meaning of lexical entries is specified by pointing to elements in the ontology. . 14 / 41

The lemon model (core) LexicalForm writtenRep:String canonicalForm form otherForm Word abstractForm Lexicon entry LexicalEntry Phrase language:String sense isSenseOf Part LexicalSense reference prefRef altRef isReferenceOf hiddenRef Ontology 15 / 41

The lemon model (argument mapping) Lexical synBehavior Frame Entry isSenseOf subsense sense synArg LexicalSense semArg Argument context:Resource propertyDomain condition:Resource propertyRange definition:Resource marker reference isReferenceOf subjOfProp Syntactic objOfProp Ontology isA Role Marker 16 / 41

Example : Form :Perlfish :predator :Heron . writtenRep="eat"@en → Herons eat perl fish. canonical form eat : Word synBehavior . . . . . . . . . . . . . . . . : TransitiveFrame partOfSpeech=verb directObject sense subject subjOfProp : Argument : LexicalSense reference objOfProp : Argument <http://example.org/OceanWildlife.owl#predator> 17 / 41

...make GF! Mapping ontology lexica to grammars 18 / 41

Roadmap Mapping ontology lexica to GF requires to capture � the ontological (semantic) level � the lexical (morpho-syntactic) level General method: 1 ontology → abstract syntax . . 2 lexical entries → concrete syntax . . 19 / 41

From an ontology to abstract syntax 1 1 K. Angelov: The abstract syntax as ontology. GFSS 2009. K. Angelov & R. Enache: Typeful Ontologies with Direct Multilingual Verbalization. CNL 2010. 20 / 41

Ontology to abstract syntax 1 cat 2 Class; 3 Individual Class; 4 5 Datatype; 6 Literal Datatype; 7 8 Statement; 9 21 / 41

Example conservationStatus . . . . . . . Species String Fish Bird 10 fun 11 Species, Fish, Bird : Class; 12 String : Datatype; 13 14 ChiemseePerlfish : Individual Fish; 15 16 conservationStatus : Individual Species 17 -> Literal String 18 -> Statement; 19 20 coerce_Fish_to_Species : Individual Fish 21 -> Individual Species; 22 22 / 41

OWL constructs Add functions for complex � classes (union, intersection, complement, restriction classes) � properties (inverse properties, property chains) Example: 1 :Endangered rdf:type owl:Restriction; owl:onProperty onto:conservationStatus ; 2 owl:hasValue "EN" . 3 4 5 � Things_with_conservationStatus_EN : Class; 23 / 41

From a lexicon to concrete syntax 24 / 41

Example Lexicon: 1 :ocean_N a lemon:Word ; 2 lexinfo:partOfSpeech lexinfo:commonNoun; 3 lemon:canonicalForm [ lemon:writtenRep "ocean"@en ]; 4 lemon:otherForm [ lemon:writtenRep "oceans"@en; lexinfo:number lexinfo:plural ]; 5 6 lemon:sense [ lemon:reference onto:Ocean ] . Concrete syntax: 1 lin Ocean = mkCN (mkN "ocean" "oceans"); 25 / 41

Example Lexicon: 1 :sea_N a lemon:Word ; 2 lexinfo:partOfSpeech lexinfo:commonNoun; 3 lemon:canonicalForm [ lemon:writtenRep "sea"@en ]; 4 lemon:otherForm [ lemon:writtenRep "seas"@en; lexinfo:number lexinfo:plural ]; 5 6 lemon:sense [ lemon:reference onto:Ocean ] . Concrete syntax: 1 lin Ocean = variants { mkCN (mkN "ocean" "oceans"); 2 mkCN (mkN "sea" "seas") 3 }; 4 26 / 41

� Individual = NP; � the Pacific Ocean � Class = cn:CN; ap:AP ; � whale � endangered � Statement = np:NP; vp:VP; vpSlash:VPSlash ; NP The finback VP lives in the Pacific Ocean . � Which ocean does NP the finback VPSlash live in ? Linearization categories lincat 27 / 41

� Class = cn:CN; ap:AP ; � whale � endangered � Statement = np:NP; vp:VP; vpSlash:VPSlash ; NP The finback VP lives in the Pacific Ocean . � Which ocean does NP the finback VPSlash live in ? Linearization categories lincat � Individual = NP; � the Pacific Ocean 27 / 41

� Statement = np:NP; vp:VP; vpSlash:VPSlash ; NP The finback VP lives in the Pacific Ocean . � Which ocean does NP the finback VPSlash live in ? Linearization categories lincat � Individual = NP; � the Pacific Ocean � Class = { cn:CN; ap:AP } ; � whale � endangered 27 / 41

Linearization categories lincat � Individual = NP; � the Pacific Ocean � Class = { cn:CN; ap:AP } ; � whale � endangered � Statement = { np:NP; vp:VP; vpSlash:VPSlash } ; � [ NP The finback ] [ VP lives in the Pacific Ocean ] . Which ocean does [ NP the finback ] [ VPSlash live in ] ? 27 / 41