cyc representing, acquiring and using knowledge dr. michael witbrock cycorp, rer d.o.o. ...

CycCycRepresenting, Acquiring and Representing, Acquiring and Using KnowledgeUsing Knowledge

Dr. Michael WitbrockCycorp, RER d.o.o.

http://cycorp.eu

[email protected]

May 24th, 2007

“People have silly reasons why computers don’t really think. The

answer is we haven’t programmed them right; they just don’t have much

common sense. There’s been only one large project to do something about that, that’s the famous Cyc

project…”- Prof. Marvin Minsky

MIT, May, 2001

http://www.cycorp.eu/

http://www.cycorp.eu/

[email protected]

Cycorp Corporate MissionCycorp Corporate Mission

1984:

Increase human capabilities by building the first true Artificial Intelligence.

Revised:

Increase human capabilities by teaching the first true Artificial Intelligence to build itself.

[email protected]

Cycorp d.o.o Corporate Cycorp d.o.o Corporate MissionMission

1984:

Increase human capabilities by building the first true Artificial Intelligence.

Further Revised:

Increase human capabilities by teaching the first true Artificial Intelligence to parts of itself

in Slovenia.

[email protected]

Thing

IntangibleThing Individual

TemporalThing

SpatialThing

PartiallyTangible

ThingPaths

SetsRelations

LogicMath

HumanArtifacts

SocialRelations,

Culture

HumanAnatomy &PhysiologyEmotion

PerceptionBelief

HumanBehavior &

Actions

ProductsDevices

ConceptualWorks

VehiclesBuildingsWeapons

Mechanical& Electrical

Devices

SoftwareLiterature

Works of ArtLanguage

AgentOrganizations

OrganizationalActions

OrganizationalPlans

Types ofOrganizations

HumanOrganizations

NationsGovernmentsGeo-Politics

Business, Military

Organizations

Law

Business &Commerce

PoliticsWarfare

ProfessionsOccupations

PurchasingShopping

TravelCommunication

Transportation& Logistics

SocialActivities

EverydayLiving

SportsRecreation

Entertainment

Artifacts

Movement

State ChangeDynamics

MaterialsParts

Statics

PhysicalAgents

BordersGeometry

EventsScripts

SpatialPaths

ActorsActions

PlansGoals

Time

Agents

Space

PhysicalObjects

HumanBeings

Organ-ization

HumanActivities

LivingThings

SocialBehavior

LifeForms

Animals

Plants

Ecology

NaturalGeography

Earth &Solar System

PoliticalGeography

Weather

Tens of thousands of Predicates between, owns, isa, beliefs

Hundreds of thousands of Concepts CityOfLjubljanaSlovenia, Witbrock, Slovenia, SlovenianLanguage

Millions of Assertions“Causes precede effects” (Forall x (Forall y (implies (causes x y) (startsAfterStartOf y x))))

The Cyc Ontology and ContentThe Cyc Ontology and Content

General Knowledge various domains

Specific data, facts, and observations about those domains

Cycorp © 2007

Cyc is…Cyc is…

The typical bird has 1 beak, 1 heart, lots of feathers,…Hearts are internal organs; feathers are external

protrusionsMost vehicles are steered by an awake, sane, adult,…

humanTangible objects can’t be in 2 (disjoint) places at onceBadly injuring a child is much worse than killing a dogCauses temporally precede (i.e., start before) their

effectsA stabbing requires 2 co-temporal and proximate

actors ◦etc., etc., etc., etc., …

Millions of facts, rules of thumb, etc. that capture human common sense about our everyday world

Cycorp © 2007

Cyc Reasons via Formal Logic Cyc Reasons via Formal Logic

Very specific information(some indirect, via SKSI)

UpperOntology

CoreTheories

Domain-SpecificTheories

( a, b ) a EVENT b EVENT causes( a, b ) precedes(

a, b )

( m, a ) m MAMMAL a ANTHRAX � causes( exposed-to( m, a ), infected-by( m, a ) )

(ist FtLaudHolyCrossERCase#403921 (caused CutaneousAnthrax (SkinLesions Ahmed_al-Haznawit)))

First Order Predicate Calculus: unambiguous; enable mechanical reasoning

Every Slovene has a president.Every Slovene has a mother.Every Slovene has a president.Every Slovene has a mother.

y.x. Slov(x) president(x,y)x.y. Slov(x) mother(x,y)y.x. Slov(x) president(x,y)x.y. Slov(x) mother(x,y)

Higher Order Logic (nth-order predicate calculus): contexts,

predicates as variables, nested modals, reflection,…

Cycorp © 2007

The Cyc Knowledge BaseThe Cyc Knowledge Base

ThingThing

IntangibleThingIntangibleThing IndividualIndividual

TemporalThingTemporalThing

SpatialThingSpatialThing

PartiallyTangibleThing


PathsPaths

SetsRelationsSetsRelations

LogicMathLogicMath

HumanArtifactsHumanArtifacts

SocialRelations,Culture


HumanAnatomy &Physiology


EmotionPerceptionBelief


HumanBehavior &Actions


ProductsDevicesProductsDevices

ConceptualWorksConceptualWorks



Mechanical& ElectricalDevices


SoftwareLiteratureWorks of Art


LanguageLanguage

AgentOrganizationsAgentOrganizations

OrganizationalActionsOrganizationalActions

OrganizationalPlansOrganizationalPlans

Types ofOrganizationsTypes ofOrganizations

HumanOrganizationsHumanOrganizations



Business, MilitaryOrganizations


LawLaw

Business &CommerceBusiness &Commerce

PoliticsWarfarePoliticsWarfare

ProfessionsOccupationsProfessionsOccupations

PurchasingShoppingPurchasingShopping

TravelCommunicationTravelCommunication

Transportation& LogisticsTransportation& Logistics

SocialActivitiesSocialActivities

EverydayLivingEverydayLiving

SportsRecreationEntertainment


ArtifactsArtifacts

MovementMovement

State ChangeDynamicsState ChangeDynamics

MaterialsPartsStatics


PhysicalAgentsPhysicalAgents

BordersGeometryBordersGeometry

EventsScriptsEventsScripts

SpatialPathsSpatialPaths

ActorsActionsActorsActions

PlansGoalsPlansGoals

TimeTime

AgentsAgents

SpaceSpace

PhysicalObjectsPhysicalObjects

HumanBeingsHumanBeings

Organ-izationOrgan-ization

HumanActivitiesHumanActivities

LivingThingsLivingThings

SocialBehaviorSocialBehavior

LifeFormsLifeForms

AnimalsAnimals

PlantsPlants

EcologyEcology

NaturalGeographyNaturalGeography

Earth &Solar SystemEarth &Solar System

PoliticalGeographyPoliticalGeography

WeatherWeather

General Knowledge about Various DomainsGeneral Knowledge about Various Domains

Specific data, facts, and observationsSpecific data, facts, and observations

Cycorp © 2007

ThingThing






PathsPaths


LogicMathLogicMath


















LanguageLanguage










LawLaw











ArtifactsArtifacts

MovementMovement










TimeTime

AgentsAgents

SpaceSpace







LifeFormsLifeForms

AnimalsAnimals

PlantsPlants

EcologyEcology




WeatherWeather

General Knowledge about TerrorismGeneral Knowledge about Terrorism

Specific data, facts, and observationsabout terrorist groups and activitiesSpecific data, facts, and observationsabout terrorist groups and activities

General Knowledge about Terrorism:Terrorist groups are capable of directing assassinations: (implies (isa ?GROUP TerroristGroup) (behaviorCapable ?GROUP AssassinatingSomeone directingAgent))…If a terrorist group considers an agent an enemy, that agent is vulnerable to an attack by that group:(implies (and (isa ?GROUP TerroristGroup) (considersAsEnemy ?GROUP ?TARGET)) (vulnerableTo ?GROUP ?TARGET TerroristAttack))

General Knowledge about Terrorism:Terrorist groups are capable of directing assassinations: (implies (isa ?GROUP TerroristGroup) (behaviorCapable ?GROUP AssassinatingSomeone directingAgent))…If a terrorist group considers an agent an enemy, that agent is vulnerable to an attack by that group:(implies (and (isa ?GROUP TerroristGroup) (considersAsEnemy ?GROUP ?TARGET)) (vulnerableTo ?GROUP ?TARGET TerroristAttack))

Cyc KB Extended w/Domain Cyc KB Extended w/Domain KnowledgeKnowledge

Cycorp © 2007

ThingThing






PathsPaths


LogicMathLogicMath


















LanguageLanguage










LawLaw











ArtifactsArtifacts

MovementMovement










TimeTime

AgentsAgents

SpaceSpace







LifeFormsLifeForms

AnimalsAnimals

PlantsPlants

EcologyEcology




WeatherWeather

General Knowledge about TerrorismGeneral Knowledge about Terrorism

Specific data, facts, and observationsabout terrorist groups and activitiesSpecific data, facts, and observationsabout terrorist groups and activities

Specific Facts about Al Qaida:(basedInRegion AlQaida Afghanistan) Al-Qaida is based in Afghanistan.(hasBeliefSystems AlQaida IslamicFundamentalistBeliefs) Al-Qaida has Islamic fundamentalist beliefs.(hasLeaders AlQaida OsamaBinLaden) Al-Qaida is led by Osama bin Laden.…(affiliatedWith AlQaida AlQudsMosqueOrganization) Al-Qaida is affiliated with the Al Quds Mosque.(affiliatedWith AlQaida SudaneseIntelligenceService) Al-Qaida is affiliated with the Sudanese Intell Service…(sponsors AlQaida HarakatUlAnsar) Al-Qaida sponsors Harakat ul-Ansar.(sponsors AlQaida LaskarJihad) Al-Qaida sponsors Laskar Jihad.…(performedBy EmbassyBombingInNairobi AlQaida) Al-Qaida bombed the Embassy in Nairobi.(performedBy EmbassyBombingInTanzania AlQaida) Al-Qaida bombed the Embassy in Tanzania.

Specific Facts about Al Qaida:(basedInRegion AlQaida Afghanistan) Al-Qaida is based in Afghanistan.(hasBeliefSystems AlQaida IslamicFundamentalistBeliefs) Al-Qaida has Islamic fundamentalist beliefs.(hasLeaders AlQaida OsamaBinLaden) Al-Qaida is led by Osama bin Laden.…(affiliatedWith AlQaida AlQudsMosqueOrganization) Al-Qaida is affiliated with the Al Quds Mosque.(affiliatedWith AlQaida SudaneseIntelligenceService) Al-Qaida is affiliated with the Sudanese Intell Service…(sponsors AlQaida HarakatUlAnsar) Al-Qaida sponsors Harakat ul-Ansar.(sponsors AlQaida LaskarJihad) Al-Qaida sponsors Laskar Jihad.…(performedBy EmbassyBombingInNairobi AlQaida) Al-Qaida bombed the Embassy in Nairobi.(performedBy EmbassyBombingInTanzania AlQaida) Al-Qaida bombed the Embassy in Tanzania.

Cyc KB Extended w/Domain Cyc KB Extended w/Domain KnowledgeKnowledge

Cycorp © 2007

CycCyc ReasoningModules

ReasoningModules

Interface to External Data Sources

Interface to External Data Sources

Cyc

API

Cyc

API

Know

led

ge

Entr

y T

ools

Know

led

ge

Entr

y T

ools

User Interface(with Natural Language Dialog)

User Interface(with Natural Language Dialog)

DataBasesDataBases

WebPagesWebPages

Text SourcesText Sources

Other KBsOther KBs

Cyc Ontology & Knowledge Base

Cyc High-level ArchitectureCyc High-level Architecture

Cycorp © 2007

Multiple Contexts and ReasonersMultiple Contexts and Reasoners

The Knowledge Base is divided into thousands of contexts by:

granularity, topic, culture, geospatial place, time,...

Cyc is not monolithic

The inference engine has more than 1,000 “agents” that attack every problem and, recursively, every sub-problem. They have specialised representations and methods to quickly solve common problems.

Cyc is not committed to any one reasoning mechanism

Soon: Distributed, Parallel ReasoningSoon: Distributed, Parallel Reasoning

Cycorp © 2007

Additional reasoning modules can include any manner of external databases, simulators, translators…

Cyc is not committed to its own reasoning mechanisms

98% of its content is marked as merely being usually true.

Reasoning in Cyc is default (gather up pro/con arguments,

and compare them).

Cyc is not monotonic

Multiple Contexts and ReasonersMultiple Contexts and Reasoners

Soon: Probabilistic ReasoningSoon: Probabilistic Reasoning

[email protected]

Goog

le b

ooks

pro

ject fi

nish

ed

Today: Acquiring KnowledgeToday: Acquiring Knowledgeamount known

rate

of

lear

ning

learning by discovery

learning via

natural language

codify & enter each piece of knowledge, by hand

Frontier of human knowledge

CYC

In this area, empirical discovery and learning via NL come together.

In this area, empirical discovery and learning via NL come together.

Crossover Point: Cyc learns faster by itself than by manual

knowledge entry

Crossover Point: Cyc learns faster by itself than by manual

knowledge entry

[email protected]

Cyc TodayCyc Today

Reasoning via deduction, abduction, and induction; access to other reasoningcapabilities (throughheuristic modules)

Growing ability to supportKnowledge Acquisition

and use via NaturalLanguage

General-purpose platform: Supports applications involving search,question answering, knowledge management, scenario generation,

situation reporting, (re-)planning, etc.

Research Platform: OpenCyc, ResearchCycResearch Platform: OpenCyc, ResearchCyc

Cyc Analytical EnvironmentCyc Analytical Environment

Michael Witbrock © Cycorp 2007

Content and RepresentationDrill-down


Cycorp © 2007

Cyc KB SamplerCyc KB Sampler

Temporal RelationsSenses of “x is a physical part of y”Senses of “x is physically in y”Events and their performers (role types)OrganizationsPropositional AttitudesBiologyMaterialsDevicesWeather

Cycorp © 2007

Temporal RelationsTemporal Relations

37 Relations Between Temporal Things

#$temporalBoundsIntersect

#$temporallyIntersects

#$startsAfterStartingOf

#$endsAfterEndingOf

#$startingDate

#$temporallyContains

#$temporallyCooriginating

#$temporalBoundsContain

#$temporalBoundsIdentical

#$startsDuring

#$overlapsStart

#$startingPoint

#$simultaneousWith

#$after

Cycorp © 2007

Temporal RelationsTemporal Relations

#$temporallyIntersectsSome of these Relations are very General, such as:

Such relations are particularly useful when they are known not to hold between a pair of individuals:

(#$not (#$temporallyIntersects ?X ?Y))

That implies all of these:(#$not (#$spouse PERSON-X PERSON-Y)) (#$not (#$consultant AGENT-X AGENT-Y)) (#$not (#$accountHolder ACCOUNT-X AGENT-Y))(#$not (#$residesInRegion AGENT-X REGION-Y)) (#$not (#$officiator EVENT-X PERSON-Y))

Cycorp © 2007

Senses of ‘Part’Senses of ‘Part’

#$parts#$intangibleParts#$subInformation#$subEvents#$physicalDecompositions#$physicalPortions

• #$physicalParts• #$externalParts• #$internalParts• #$anatomicalParts• #$constituents• #$functionalPart

Cycorp © 2007

Senses of ‘In’Senses of ‘In’

Can the inner object leave by passing between members of the outer group?•Yes -- Try #$in-Among

Cycorp © 2007


Does part of the inner objectstick out of the container?

◦ None of it. -- Try #$in-ContCompletely

◦ Yes -- Try #$in-ContPartially

◦ No -- Try • #$in-ContClosed

◦ If the container were turned around could the contained object fall out?

– Yes -- Try #$in-ContOpen

Cycorp © 2007


Can it be removed by pulling, if enough force is used, without damaging

either object?– No -- Try #$in-Snugly

or #$screwedIn

Is it attached to the inside of the outer object?– Yes -- Try

#$connectedToInside

Does the inner objectstick into the outer object?–Yes – Try #$sticksInto

Cycorp © 2007

Event TypesEvent Types

#$PhysicalStateChangeEvent #$TemperatureChangingProcess #$BiologicalDevelopmentEvent #$ShapeChangeEvent #$MovementEvent #$ChangingDeviceState #$GivingSomething #$DiscoveryEvent

#$Cracking #$Carving #$Buying #$Thinking #$Mixing #$Singing #$CuttingNails #$PumpingFluid

11,000 more

Cycorp © 2007

#$performedBy #$causes-EventEvent #$objectPlaced #$objectOfStateChange #$outputsCreated #$inputsDestroyed #$assistingAgent #$beneficiary

#$fromLocation #$toLocation #$deviceUsed #$driverActor #$damages #$vehicle #$providerOfMotiveForce

#$transportees Over 400 more.

Relations Between Events and ParticipantsRelations Between Events and Participants

Cycorp © 2007

Here are some roles for Attack874 isa: TerroristAttack. performedBy: JihadGroup. deviceUsed: Bomb8388. eventOccursAt: CityOfLondonEngland. victim: Person9399. victim: Person52666. assistingAgent: AlQaeda. objectsDestroyed: Structure2990. objectsDestroyed: Vehicle523452.

Representation of A Sample EventRepresentation of A Sample Event

Natural LanguageDrill-down


Cycorp © 2007

Cyc NL LexiconCyc NL Lexicon

Cycorp © 2007

Constant : Coke-TheWordisa : EnglishWord

Mt : EnglishMtsingular : “coke” pnSingular : “Coke” massNumber : “coke” pnMassNumber : “Coke”

(denotation Coke-TheWord ProperCountNoun 0 (ServingFn CocaCola))(denotation Coke-TheWord ProperMassNoun 0 CocaCola)(denotation Coke-TheWord MassNoun 0 Cocaine-Powder)(denotation Coke-TheWord MassNoun 2 ColaSoftDrink)(denotation Coke-TheWord SimpleNoun 0 (ServingFn ColaSoftDrink))

Lexical Entry Example: CokeLexical Entry Example: Coke

SLANG

SLANG

SLANG

Cycorp © 2007

Lexical Entry Example: EatLexical Entry Example: Eat

(verbSemTrans Eat-TheWord 0 TransitiveNPCompFrame(and (isa :ACTION EatingEvent) (performedBy :ACTION :SUBJECT) (inputsDestroyed :ACTION :OBJECT)))

Constant: Eat-TheWordisa: EnglishWord

Mt: EnglishMtinfinitive: “eat” pastTense: “ate”perfect: “eaten” agentive-Sg: “eater”

(subcatFrame Eat-TheWord Verb 0 TransitiveNPCompFrame)

Document TaggingDocument Tagging

…

Document Tagging

Entire Cyc KBEntire Cyc KB

Military TaxonomyMilitary Taxonomy

Probabilistic Concept TaggingProbabilistic Concept Tagging

“The plants that produced the cranes that NASA deployed in space in the 1990s are in Canada.”

The plants (#$FactoryBuildingComplex 0.8817 #$Plant 0.0967) that produced (#$Production-Generic 0.6017) the cranes (#$Crane-MotorizedDevice 0.9387 #$Crane-Bird 0.0408) that NASA (#$NASA) deployed (#$DeployingMaterial) in space (#$OuterSpace 0.51 #$SpaceInAHOC 0.1473 #$ReservedSpaceRegion 0.0459 #$Area 0) in the 1990s ((#$DecadeFn 199) 1) are in Canada (#$Canada 1).

Knowledge for DisambiguationKnowledge for Disambiguation

Simple Example: #$isa“… natural resources, of which oil and

diamonds are the most relevant.”

“oil”• #$Oil• #$Petroleum-CrudeOil• #$ArtistOilPaint• #$PetroleumProduct

“oil”• #$Oil• #$Petroleum-CrudeOil• #$ArtistOilPaint• #$PetroleumProduct

“natural resources”• #$NaturalResourceType“diamonds”

• #$Diamond• #$Diamond-Gem• #$Diamonds-Suit

“diamonds”• #$Diamond• #$Diamond-Gem• #$Diamonds-Suit

#$isa licence#$isa licence

Looks for collections in Looks for collections in the text of which a given the text of which a given

object is an instanceobject is an instance

#$siblingsWRTType #$siblingsWRTType licencelicence

Looks for collections in Looks for collections in the text that share a the text that share a

typetype

Knowledge Driven DisambiguationKnowledge Driven Disambiguation

Example: “common sense”“The heart pumps blood to the lungs.”

“heart”• #$Heart-Suit• #$Heart-LocusOfFeeling• #$CenterOfRegion• #$Heart“pumps”• #$PumpingFluid• #$Pumping-MakingSomething Available

#$typeBehaviorCapable#$typeBehaviorCapable

Are there any pairs Are there any pairs <C1,C2> such that <C1,C2> such that

every C1 is capable of every C1 is capable of playing a role in an playing a role in an event of type C2?event of type C2?

Cyc Knows: The heart is a kind of Cyc Knows: The heart is a kind of pump.pump.Cyc Knows: Every pump can pump Cyc Knows: Every pump can pump fluid.fluid.

Cycorp © 2007

Noun CompoundsNoun CompoundsMore Complex ParsingMore Complex Parsing

Renaissance Artists

Kind of TimeInterval

Noun Form: not plural

Kind of Agent-Generic

Noun form

Bronze Age Farmers

(SubcollectionOfWithRelationToFn Artist activeDuringPeriod TheRenaissance)

(SubcollectionOfWithRelationToFn Farmer activeDuringPeriod TheBronzeAge)

+-------------------------------------------Xp-------------------------------------------+ +------------Wd------------+ +--------------------MVp---------------------+ | | +--------A--------+ | +------Jp-----+----Mp----+ | | | | +--G--+--G-+--Ss--+---Os---+--Mp-+ +--Dmcn--+ +N Sa+ +-Js-+ | | | | | | | | | | | | | | | | LEFT Royal.a Dutch Shell Plc halted.v output.n of 455,000 barrels.n a day.p in Nigeria .

(#$and (#$isa (#$TheFn #$DecreaseEvent) (#$DecreaseInValueReturnedByFn (#$ExportRateOfByFn #$Petroleum-CrudeOil) #$Nigeria)) (#$doneBy (#$TheFn #$DecreaseEvent) #$RoyalDutchShell) (#$quantityChangeAmount (#$TheFn #$DecreaseEvent) (#$BarrelsPerDay 455000)))

+-------------------------------------------Xp-------------------------------------------+ +------------Wd------------+ +--------------------MVp---------------------+ | | + | +------Jp-----+ | | | +-----------+--Ss--+---Os---+--Mp-+ + +-Js-+ | | | | | | | | | | LEFT [Agent] halted.v output.n of [Quantity] in [Locn] .

(#$and (#$isa (#$TheFn #$DecreaseEvent) (#$DecreaseInValueReturnedByFn (#$ExportRateOfByFn #$Petroleum-CrudeOil) [Locn])) (#$doneBy (#$TheFn #$DecreaseEvent) [Agent]) (#$quantityChangeAmount (#$TheFn #$DecreaseEvent) [Quantity]))

Petróleos de Venezuela S.A. halted output of 760 000 barrels a week in Maracaibo.

(#$and (#$isa (#$TheFn #$DecreaseEvent) (#$DecreaseInValueReturnedByFn (#$ExportRateOfByFn #$Petroleum-CrudeOil) #$CityOfMaracaiboVenezuela)) (#$doneBy (#$TheFn #$DecreaseEvent) #$PetroleosdeVenezuelaSA (#$quantityChangeAmount (#$TheFn #$DecreaseEvent) (#$BarrelsPerDay 760000)))

Knowledge AcquisitionDrill-down


Mohamed Atta

No page foundNo page found Hypothesis not logically consistent

Hypothesis not logically consistent

Uninformative sentence

Uninformative sentence

Unable to parseUnable to parse

(#$genls #$Polygraph #$Device-Physical)

Automatically Adding to the ModelAutomatically Adding to the Model

… Klingberg contacted the USSR for the first time in 1957, and soon after that he started his espionage activity. Israel's foreign and domestic intelligence agencies, Mossad and Shin Bet, started suspecting Klingberg of espionage, but shadowing brought no results. At one point, the scientist also successfully passed

the polygraph test…

Device-Physical

Polygraph

genls

Cycorp © 2007


Query

“What are symptoms of Whooping Cough?”

(symptomOfAilment WhoopingCough ?SYMP )

“What are symptoms of Whooping Cough?”

(symptomOfAilment WhoopingCough ?SYMP )

NL Generation

“A symptom of whooping cough is ___”

“Whooping cough can cause ___”

“A symptom of Pertussis Bordetella is ___”

“Symptoms (such as ____) of whooping cough”

“A symptom of whooping cough is ___”

“Whooping cough can cause ___”

“A symptom of Pertussis Bordetella is ___”

“Symptoms (such as ____) of whooping cough”

Partial English sentences

Learning FactsLearning Factsby Searchby Search

C. Matuszek, R.C. Kahlert , M Witbrock FACTory © Cycorp 2007

Parsing ResultsParsing Results

“… symptoms of pertussis such as fever and a dry cough …”

Looking for something that matches the argument constraints on the predicate…

(symptomOfAilment WhoopingCough Fever)(symptomOfAilment WhoopingCough Coughing-

AilmentCondition)

Parse back into existing CycL concepts

Parsing ResultsParsing Results

PiracyEvent 1

Group ofPirates 1Group ofPirates 1

SomaliaSomalia

January20, 2006January

20, 2006

MV DeltaRanger

MV DeltaRanger

perpetrator

dateOfEvent

intendedAttackTargetseventOccursNear

intendedAttackTargets

PiracyEvent 2


PhilippinesPhilippines


15, 2006

MV ManChu Yi

MV ManChu Yi

perpetratordateOfEvent

eventOccursNear

PiracyEvent 3


NigeriaNigeria

February18, 2006February18, 2006

perpetrator

dateOfEvent

eventOccursNear

SpeedBoat 1SpeedBoat 1

deviceUsed

Given a set of events that Cyc already knows about…

…recognize new instances of that event type in textMalacca Straits:

On 17 April 2006, a Malaysian fishing vessel was attacked by armed pirates at approximately nine nautical miles off Parit Haji Baki coast in the Malacca Straits at about 0200 Hrs LT. Six pirates armed with guns in a speedboat closed in rapidly and opened fire at the fishing vessel underway. Several shots hit the side of the vessel but the crew escaped injuries. The fishing vessel crew lodged a police report.

Malacca Straits:


NewPiracyEvent

P(deviceUsed) = 1/3 = 0.33p(perpetrator) = 3/3 = 1.0p(dateOfEvent) = 3/3 = 1.0p(eventOccursNear) = 3/3 = 1.0p(intendedAttackTargets) = 2/3 = 0.66

P(deviceUsed) = 1/3 = 0.33p(perpetrator) = 3/3 = 1.0p(dateOfEvent) = 3/3 = 1.0p(eventOccursNear) = 3/3 = 1.0p(intendedAttackTargets) = 2/3 = 0.66

PiracyEvent 1

perpetrator

dateOfEvent



PiracyEvent 2


eventOccursNear

PiracyEvent 3

perpetrator

dateOfEvent

eventOccursNear

deviceUsed

determines appropriate relations for event type

that occur in >1/2 of the known events.

NewPiracyEvent

perpetrator


dateOfEvent

eventOccursNear

Malacca Straits:


Malacca Straits:


NewPiracyEvent

PiracyEvent 1


SomaliaSomalia


20, 2006

MV DeltaRanger

MV DeltaRanger

perpetrator

dateOfEvent



PiracyEvent 2




15, 2006

MV ManChu Yi

MV ManChu Yi


eventOccursNear

PiracyEvent 3


NigeriaNigeria

February18, 2006February18, 2006

perpetrator

dateOfEvent

eventOccursNear

SpeedBoat 1SpeedBoat 1

deviceUsed

…look at role fillers for known events…

and find similar types of concepts mentioned in the text.

perpetrator


dateOfEvent

eventOccursNear

??????

??????

??????

??????

Malacca Straits:


Malacca Straits:


MalaysiaMalaysia

PiratesPirates

SomePirateSomePirate

Parit HajiBaki

Parit HajiBaki

MalaccaStraits

MalaccaStraits

SpeedBoatsSpeedBoats

SomeSpeedBoat

SomeSpeedBoat

PolicePolice

SomePoliceOfficer

SomePoliceOfficer

DatesDates VehiclesVehicles PeoplePeople

ThingsThings

PlacesPlaces

April 17,2006

April 17,2006

People& Org.sPeople& Org.s

Concepts in Cyc’s ontology are found in the text

Malaysia

Pirates

SomePirate

Parit HajiBaki

MalaccaStraits

SpeedBoats

SomeSpeedBoat

Police

SomePoliceOfficer


ThingsThings

PlacesPlaces

April 17,2006

Org.sOrg.s


Group ofPirates 1

Somalia

January20, 2006

MV DeltaRanger

Group ofPirates 3

February18, 2006

Group ofPirates 2

PhilippinesJanuary

15, 2006MV ManChu Yi

SpeedBoat 1

Groupsof

Pirates

Groupsof

Pirates

The concepts associated with the known events are alsomapped to the ontology.

P(isa(X,Thing) | (eventOccursNear EVENT X)) = 1P(isa(X,Place) | (eventOccursNear EVENT X)) = 1P(isa(X,Date) | (eventOccursNear EVENT X)) = 0P(isa(X,Vehicle) | (eventOccursNear EVENT X)) = 0P(isa(X,Person or Org.) | (eventOccursNear EVENT X)) = 0P(isa(X,Person) | (eventOccursNear EVENT X)) = 0P(isa(X,Org.) | (eventOccursNear EVENT X)) = 0P(isa(X,Group of Pirates) | (eventOccursNear EVENT X)) = 0

P(isa(X,Thing) | (eventOccursNear EVENT X)) = 1P(isa(X,Place) | (eventOccursNear EVENT X)) = 1P(isa(X,Date) | (eventOccursNear EVENT X)) = 0P(isa(X,Vehicle) | (eventOccursNear EVENT X)) = 0P(isa(X,Person or Org.) | (eventOccursNear EVENT X)) = 0P(isa(X,Person) | (eventOccursNear EVENT X)) = 0P(isa(X,Org.) | (eventOccursNear EVENT X)) = 0P(isa(X,Group of Pirates) | (eventOccursNear EVENT X)) = 0


ThingsThings

PlacesPlaces

Org.sOrg.s


SomaliaSomalia


Collections are associated with each relation…

NewPiracyEvent eventOccursNear

??????

The most relevant Collections are those where the probability of seeing them is high for concepts that have this relation toan event of this type, and have low probability of being seenotherwise.

Malaysia

Pirates

SomePirate

Parit HajiBaki

MalaccaStraits

SpeedBoats

SomeSpeedBoat

Police

SomePoliceOfficer


ThingsThings

PlacesPlaces

April 17,2006

Org.sOrg.s


Groupsof

Pirates

Groupsof

Pirates

Probabilities can be estimated for extracted concepts…

to measure how well they fit the relation.

NewPiracyEvent

eventOccursNear

p(Malacca Straits) = 1p(Malaysia) = 1p(Parit Haji Baki) = 1p(April 17, 2006) = 0p(Speed Boats) = 0P(Some Speed Boat) = 0…

p(Malacca Straits) = 1p(Malaysia) = 1p(Parit Haji Baki) = 1p(April 17, 2006) = 0p(Speed Boats) = 0P(Some Speed Boat) = 0…

MalaysiaMalaysia

Parit HajiBaki

Parit HajiBaki

MalaccaStraits

MalaccaStraits

eventOccursNear

After repeating this process for every relation, choosingrelation/concept pairs with >0.5 probability, a potentialevent has been extracted from the text.

NewPiracyEvent

SomeSpeedBoat

SomeSpeedBoat

April 17,2006

April 17,2006

eventOccursNear

MalaysiaMalaysia

Parit HajiBaki

Parit HajiBaki

MalaccaStraits

MalaccaStraits


dateOfEvent

Malacca Straits:


Malacca Straits:


Probabilities for each relation/concept pair canthen be used to estimate the overall probability of theextracted event being correct.

April 17,2006(1.0)

April 17,2006(1.0)

PiracyEvent(0.67)

SomeSpeed

Boat (1.0)

SomeSpeed

Boat (1.0)

eventOccursNear (1.0)

Malaysia(1.0)

Malaysia(1.0)

Parit HajiBaki (1.0)Parit HajiBaki (1.0)

MalaccaStraits(1.0)

MalaccaStraits(1.0)

intendedAttackTargets (0.67)

dateOfEvent (1.0)

Malacca Straits:


Malacca Straits:


Initial ResultsInitial Results

C. Matuszek, R.C. Kahlert FACTory © Cycorp 2006

Test corpus of 27 piracy documents.Extractor found 578 relation/concept

pairs.34.78% (201) were correct.Good enough to feed human validation

tools for partially automated data entry.

Using Human FeedbackUsing Human Feedback

By giving the extractor feedback about what concepts it got correct and incorrect, the precision of the extractor can be greatly increased.

In initial experiments, giving feedback on the 27 piracy paragraphs raised precision from .39 to .61 using 2-fold cross-validation.

Wrap-upWrap-up

Large vocabularies with detailed semantics are useful

More and more of the conceptual structure and knowledge will be automatically learned

The more you know, the less you need to understand

Detailed knowledge really is needed for meaningful reasoning

© Cycorp 2007

cyc representing, acquiring and using knowledge dr. michael witbrock cycorp, rer d.o.o. ...

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