A Knowledge-Rich Approach to Understanding Text about Aircraft Systems
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Transcript of A Knowledge-Rich Approach to Understanding Text about Aircraft Systems
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A Knowledge-Rich Approach to Understanding Text about Aircraft
Systems
Peter ClarkLisbeth Duncan
Heather HolmbackTom Jenkins
John ThompsonBoeing Engineering and Information Technology
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Overview• Situation: Using a hand-built, airplane knowledge-base
(KB) at Boeing (e.g., for concept-based search)
• Goal: Extend this KB by processing text:
• from airplane training manuals
• directly from an aerospace engineer
• Target: airplane parts, connections, and behaviors
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Challenge• Interpretation of text requires background knowledge
– author trying to convey a model to the reader– only some parts of this are explicitly stated in text– rest is assumed to be already known to the reader
“The hydraulic system supplies power to the
rudder.”
HydraulicSystem Rudder
Supply
Power
Powered-System
Script
Consume Transmit
Conduit
Airplane
source sink
behavior
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Approach• Use an aerospace knowledge base (KB):
– Taken from an earlier project and extended– Contains general models about what might be said
• Contains general knowledge of aircraft and systems• Doesn’t know details of specific aircraft
• Text interpretation = specializing and refining this background knowledge
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Constraints on the Scope1. Working with restricted sublanguage of English
– Simple, declarative sentences– Regular, “boring” style
“The hydraulic system supplies power to the rudder.”“A ripple damper smooths the pump pressure output.”“The EDP is on the left side of the engine main gearbox.”“The gearbox turns the EDP when the engine turns.”
2. Constrained domain (aircraft systems)– Reduces vocabulary, background KB
3. Domain of mechanical artifacts– Simple statements about structure and behavior
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KB
777-200-Airplane
ApproachUser specifies topic (eg. “777-200-Airplane”)
Tail
PoweredSystem
Rudder
VerticalStabilizer
PowerSource
Supplying
FuselageWing
Flap
parts
parts sourcesink script
systems
parts
purpose
connects
agentrecipient
Initial (general) representation of airplane built.
“The hydraulic system supplies
power to the rudder.”
Text is provided.
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777-200-Airplane
“The hydraulic system supplies
power to the rudder.”
Tail
PoweredSystem
Rudder
VerticalStabilizer
PowerSource
Supplying
FuselageWing
Flap
KB
parts
parts sourcesink script
systems
parts
purpose
connects
agentrecipient
ApproachThen:1. Text NLP structure
Rudder HydraulicSystem
Supplying
Power
recipient
object
agent
Stage 1
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777-200-Airplane
“The hydraulic system supplies
power to the rudder.”
Tail
PoweredSystem
Rudder
VerticalStabilizer
PowerSource
Supplying
FuselageWing
FlapRudder Hydraulic
System
Supplying
Power
KB
?
recipient
object
agent
parts
parts sourcesink script
systems
parts
purpose
connects
agentrecipient
ApproachThen:1. Text NLP structure2. Match NLP structure with airplane repn.
Stage 1 Stage 2
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777-200-Airplane
“The hydraulic system supplies
power to the rudder.”
Tail
PoweredSystem
Rudder
VerticalStabilizer
Supplying
FuselageWing
FlapRudder Hydraulic
System
Supplying
Power
KB
HydraulicSystem
Power
ApproachThen:1. Text NLP structure2. Match NLP structure with airplane repn.
Unify the matching structures.
recipient
object
agent
parts
parts sourcesink script
systems
parts
purpose
connects
Stage 1 Stage 2
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777-200-Airplane
Tail
PoweredSystem
VerticalStabilizer
FuselageWing
Flap
KB
parts
parts sourcesink script
systems
parts
purpose
connects
Stage 2
The Knowledge Base
Rudder PowerSource
Supplyingagentrecipient
“The hydraulic system supplies
power to the rudder.”
Rudder HydraulicSystem
Supplying
Power
recipient
object
agent
Stage 1
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The Knowledge Base• ~500 concepts, ~1500 axioms• Mainly airplane parts, behaviors, and connections• Axioms converted to prototypes (graph structures)
Axiom: “Every airplane has a fuselage, and a tail connected to the fuselage.”
(every Airplane has (parts ((a Fuselage) (a Tail with (connected-to (the Fuselage parts of Self))))
Airplane
Fuselage Tail
parts
connected-to
Prototype (sketch)
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Inference: Building the Initial Airplane Representation
777-200-Airplane
Tail
Airplane
Fuselage Tailparts
VerticalStabilizer
HorizontalStabilizer
parts
Flight
Takeoff Cruise Land
Flight
behavior
HorizontalStabilizer
parts
VerticalStabilizer
subevents
Takeoff Cruise Land
Fuselage Tail
parts
connected-to
behavior
Flight
Axioms in KB: Airplane representation:
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KB
777-200-Airplane
Tail
PoweredSystem
Rudder
VerticalStabilizer
PowerSource
Supplying
FuselageWing
Flap
parts
parts sourcesink script
systems
parts
purpose
connects
agentrecipient
“The hydraulic system supplies
power to the rudder.”
Stage 1:Text to NLP Structure
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777-200-Airplane
“The hydraulic system supplies
power to the rudder.”
Tail
PoweredSystem
VerticalStabilizer
FuselageWing
FlapRudder Hydraulic
System
Supplying
Power
KB
recipient
object
agent
parts
parts sourcesink script
systems
parts
purpose
connects
Stage 1
Stage 1:Text to NLP Structure
Rudder PowerSource
Supplyingagentrecipient
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Stage 1: Text to NLP Structure• Superficial linguistic variations normalized • Add initial semantic interpretation
• Commits to: overall parse/syntactic configuration, word senses• May underspecify: some semantic relationships (e.g., modifiers)
Rudder HydraulicSystem
Supplying
Power
recipient
object
agent
Abstract & rewrite
“The hydraulic system supplies
power to the rudder.” Parse &
semantic analysis
Supply_1[sing,pres,3S]
To_5
HydraulicSystem_1
[sing,N]
The_1[det]
delim
recipient
range
object
causer
delim
Power_1[sing,mass]
Rudder_1[sing,N]
The_1[det]
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777-200-Airplane
“The hydraulic system supplies
power to the rudder.”
Tail
PoweredSystem
VerticalStabilizer
FuselageWing
FlapRudder Hydraulic
System
Supplying
Power
KB
recipient
object
agent
parts
parts sourcesink script
systems
parts
purpose
connects
Stage 1 Rudder PowerSource
Supplyingagentrecipient
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777-200-Airplane
Tail
PoweredSystem
VerticalStabilizer
FuselageWing
Flap
parts
parts sourcesink script
systems
parts
purpose
connects
Rudder PowerSource
Supplyingagentrecipient
“The hydraulic system supplies
power to the rudder.”
Rudder HydraulicSystem
Supplying
Power
recipient
object
agent
Stage 1
?
Stage 2
KBStage 2: Match NLP Structure with Airplane Representation
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Stage 2: Match with Airplane Representation• Goal: Integrate text into airplane representation• Approach: find matching (subsuming) structure(s)
Rudder HydraulicSystem
Supplying
Power
recipient
object
agentRudder Power
Source
Supplyingagentrecipient
… ……
Text KB (Topic airplane representation)
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Stage 2: Match with Airplane Representation• Goal: Integrate text into airplane representation• Approach: find matching (subsuming) structure(s)• If match found, unify the two structures together
Rudder HydraulicSystem
Supplying
Power
recipient
object
agentRudder Power
Source
Supplyingagentrecipient
… ……
Text KB (Topic airplane representation)
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Stage 2: Match with Airplane Representation• Goal: Integrate text into airplane representation• Approach: find matching (subsuming) structure(s)• If match found, unify the two structures together
Rudder HydraulicSystem
Supplying
Power
recipient
object
agentRudder Power
Source
Supplyingagentrecipient
… ……
Rudder HydraulicSystem
Supplyingagentrecipient
…
Power
object
… …
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KB expects:
RudderPowerSource
Supplying Power“The hydraulic system supplies power to the rudder.”
But text may deviate with:
RudderHydraulicSystem
Providing Power
“The hydraulic system provides power to the rudder.”
1. Synonyms
RudderHydraulicSystem
Powering
“The hydraulic system powers the rudder.”
2. Contractions
Rudder
HydraulicSystem
Be
Supplier
Power
“The hydraulic system is the supplier of power for the rudder.”
3. Roles
4. …
Matching Problem 1:Linguistic Variation
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• Use simple transformation rules to modify NLP structure• No match transform and re-search for a match
RudderHydraulicSystem
Supplying Power
RudderHydraulicSystem
Providing Powersynonym
Rudder
HydraulicSystem
Be
Supplier
Power
role
RudderHydraulicSystem
Powering
contraction/ expansion
Matching Problem 1:Linguistic Variation
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Matching Problem 2:Expression of Implied Facts
• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
Explicit facts:
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”
Explicit facts:
Matching Problem 2:Expression of Implied Facts
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”“The pedal pulls a cable.”
Explicit facts:
Matching Problem 2:Expression of Implied Facts
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”“The pedal pulls a cable.”“The cable moves the rudder.”
Explicit facts:
Matching Problem 2:Expression of Implied Facts
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”“The pedal pulls a cable.”“The cable moves the rudder.”
Explicit facts:
Inference Rule:If A does X, and X causes Ythen add A does Y.
Matching Problem 2:Expression of Implied Facts
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”“The pedal pulls a cable.”“The cable moves the rudder.”
Implied facts:
Move
object
agent
instr-ument.
“The pilot moves the rudder using the pedal.”
Matching Problem 2:Expression of Implied Facts
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• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
Rudder
Pedal
Pilot
Cable
Press MovePull
Rudder Control System
Script
objectagent behavior
subeventsagent
object agent
object
“The pilot presses the pedal.”“The pedal pulls a cable.”“The cable moves the rudder.”
Implied facts:
Move
object
agent
instr-ument.
“The pilot moves the rudder using the pedal.”
“The pedal moves the rudder using the cable.”
Move
objectinstrument
agent
Matching Problem 2:Expression of Implied Facts
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Matching Problem 2:Expression of Implied Facts
• Problem:– Not all airplane facts are explicit in the KB structures– If user refers to an implied fact, matcher will not find it
• Approach:– Match text against an extended version of the KB– Extensions generated on demand
Airplane representation:
Explicit facts
Implied facts
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Status and Assumptions• While some components are mature, only complete
throughput for a small number of sentences • Relies on strong expectations from the KB
– Everything that might be said is encompassed by KB• Assumes stage 1 output is correct• Assumes a single model of the airplane is described
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Challenges…• Inaccurate knowledge
– “The pump supplies a source of power to the rudder.”• Simplifications/multiple models
– “There are three hydraulic systems in the 777-200.”– “The flight control surfaces steer the airplane.”
• Fluctuating (“fuzzy”) concept boundaries– “hydraulic system” includes controlled devices (eg rudder)?
• Ambiguities not locally resolvable– “The EDP is attached to the airplane’s engine.”
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Summary• Goal: extend an airplane KB from text
• Use of background knowledge can help:
– constrains possible interpretations
– provide the surrounding context
• Presented a simple model of how this can be done:
– text interpretation = iterative refinement of a representation
– use of graph matching and unification