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A Knowledge-Rich Approach to Understanding Text about Aircraft Systems Peter Clark Lisbeth Duncan Heather Holmback Tom Jenkins John Thompson Boeing Engineering and Information Technology Overview

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a knowledge rich approach to understanding text about aircraft systems

A Knowledge-Rich Approach to Understanding Text about Aircraft Systems

Peter Clark

Lisbeth Duncan

Heather Holmback

Tom Jenkins

John Thompson

Boeing Engineering and Information Technology

overview
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
challenge

Airplane

Powered-System

source

Script

sink

behavior

Hydraulic

System

Rudder

“The hydraulic system supplies power to the rudder.”

Consume

Transmit

Supply

Conduit

Power

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
approach
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
constraints on the scope
Constraints on the Scope
  • 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.”

  • Constrained domain (aircraft systems)
    • Reduces vocabulary, background KB
  • Domain of mechanical artifacts
    • Simple statements about structure and behavior
slide6

Approach

Initial (general) representation of airplane built.

Text is provided.

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

connects

sink

source

parts

script

Power

Source

Rudder

recipient

agent

Supplying

KB

User specifies topic (eg. “777-200-Airplane”)

slide7

Approach

Hydraulic

System

Rudder

recipient

agent

Supplying

Stage 1

object

Power

KB

  • Then:
  • Text  NLP structure

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

connects

sink

source

parts

script

Power

Source

Rudder

recipient

agent

Supplying

slide8

Approach

KB

  • Then:
  • Text  NLP structure
  • Match NLP structure with airplane repn.

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Stage 2

Power

Source

object

Rudder

Power

recipient

agent

?

Supplying

approach9

KB

Approach

Then:

  • Text  NLP structure
  • Match NLP structure with airplane repn.

Unify the matching structures.

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Stage 2

Hydraulic

System

object

Rudder

Power

Supplying

Power

the knowledge base

KB

The Knowledge Base

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Stage 2

Power

Source

object

Rudder

Power

recipient

agent

Supplying

the knowledge base11

Axiom:“Every airplane has a fuselage, and a tail connected to the fuselage.”

Prototype (sketch)

Airplane

parts

(every Airplane has

(parts ((a Fuselage)

(a Tail with

(connected-to

(the Fuselage parts of Self))))

Fuselage

Tail

connected-to

The Knowledge Base
  • ~500 concepts, ~1500 axioms
  • Mainly airplane parts, behaviors, and connections
  • Axioms converted to prototypes (graph structures)
inference building the initial airplane representation

parts

Fuselage

Tail

connected-to

parts

behavior

Vertical

Stabilizer

Horizontal

Stabilizer

Flight

subevents

Takeoff

Cruise

Land

Inference: Building the Initial Airplane Representation

Axioms in KB:

Airplane representation:

Airplane

777-200-Airplane

behavior

parts

Fuselage

Tail

Flight

Tail

parts

Vertical

Stabilizer

Horizontal

Stabilizer

Flight

Takeoff

Cruise

Land

slide13

Stage 1:Text to NLP Structure

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

connects

sink

source

parts

script

Power

Source

Rudder

recipient

agent

Supplying

KB

stage 1 text to nlp structure

KB

Stage 1:Text to NLP Structure

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Power

Source

object

Rudder

Power

recipient

agent

Supplying

stage 1 text to nlp structure15

Supply_1

[sing,pres,3S]

object

recipient

Hydraulic

System

Rudder

causer

Power_1

[sing,mass]

To_5

recipient

agent

range

Hydraulic

System_1

[sing,N]

Parse & semantic analysis

Supplying

Rudder_1

[sing,N]

Abstract & rewrite

object

delim

delim

Power

The_1

[det]

The_1

[det]

Stage 1: Text to NLP Structure
  • Superficial linguistic variations normalized
  • Add initial semantic interpretation

“The hydraulic system supplies power to the rudder.”

  • Commits to: overall parse/syntactic configuration, word senses
  • May underspecify: some semantic relationships (e.g., modifiers)
slide16

KB

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Power

Source

object

Rudder

Power

recipient

agent

Supplying

slide17

Stage 2: Match NLP Structure with Airplane Representation

KB

777-200-Airplane

purpose

parts

systems

Wing

Tail

Fuselage

parts

Hydraulic

System

Rudder

Vertical

Stabilizer

Powered

System

“The hydraulic system supplies power to the rudder.”

Flap

recipient

agent

connects

sink

source

parts

script

Supplying

Stage 1

Stage 2

Power

Source

object

Rudder

Power

recipient

agent

?

Supplying

stage 2 match with airplane representation

Hydraulic

System

Rudder

Power

Source

Rudder

recipient

agent

recipient

agent

Supplying

Supplying

object

Power

Text

KB (Topic airplane representation)

Stage 2: Match with Airplane Representation
  • Goal: Integrate text into airplane representation
  • Approach: find matching (subsuming) structure(s)
stage 2 match with airplane representation19

Hydraulic

System

Rudder

Power

Source

Rudder

recipient

agent

recipient

agent

Supplying

Supplying

object

Power

Text

KB (Topic airplane representation)

Stage 2: Match with Airplane Representation
  • Goal: Integrate text into airplane representation
  • Approach: find matching (subsuming) structure(s)
  • If match found, unify thetwo structures together
stage 2 match with airplane representation20

Hydraulic

System

Rudder

recipient

agent

Supplying

object

Power

Stage 2: Match with Airplane Representation
  • Goal: Integrate text into airplane representation
  • Approach: find matching (subsuming) structure(s)
  • If match found, unify thetwo structures together

Hydraulic

System

Rudder

Power

Source

Rudder

recipient

agent

recipient

agent

Supplying

Supplying

object

Power

slide21

Matching Problem 1:Linguistic Variation

But text may deviate with:

1. Synonyms

Providing

Power

“The hydraulic system provides power to the rudder.”

Hydraulic

System

Rudder

2. Contractions

Powering

“The hydraulic system powers the rudder.”

Hydraulic

System

Rudder

3. Roles

Be

“The hydraulic system is the supplier of power for the rudder.”

Supplier

Hydraulic

System

Power

Rudder

KB expects:

Supplying

Power

“The hydraulic system supplies power to the rudder.”

Power

Source

Rudder

4. …

slide22

synonym

Providing

Power

Supplying

Power

Hydraulic

System

Rudder

Hydraulic

System

Rudder

role

contraction/ expansion

Be

Supplier

Hydraulic

System

Powering

Power

Rudder

Hydraulic

System

Rudder

Matching Problem 1:Linguistic Variation

  • Use simple transformation rules to modify NLP structure
  • No match  transform and re-search for a match
matching problem 2 expression of implied facts

Explicit facts:

Rudder Control System

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

Press

Pull

Move

agent

object

Pedal

Cable

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
matching problem 2 expression of implied facts24
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

Explicit facts:

Rudder Control System

“The pilot presses the pedal.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

Press

Pull

Move

agent

object

Pedal

Cable

matching problem 2 expression of implied facts25
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

Explicit facts:

Rudder Control System

“The pilot presses the pedal.”

“The pedal pulls a cable.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

Press

Pull

Move

agent

object

Pedal

Cable

matching problem 2 expression of implied facts26
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

Explicit facts:

Rudder Control System

“The pilot presses the pedal.”

“The pedal pulls a cable.”

“The cable moves the rudder.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

Press

Pull

Move

agent

object

Pedal

Cable

matching problem 2 expression of implied facts27
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

Explicit facts:

Rudder Control System

“The pilot presses the pedal.”

“The pedal pulls a cable.”

“The cable moves the rudder.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

Press

Pull

Move

Inference Rule:

If A does X, and X causes Y

then add A does Y.

agent

object

Pedal

Cable

matching problem 2 expression of implied facts28
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

Implied facts:

Rudder Control System

“The pilot presses the pedal.”

“The pedal pulls a cable.”

“The cable moves the rudder.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

“The pilot moves the rudder using the pedal.”

Press

Pull

Move

object

agent

object

instr-

ument.

agent

Move

Pedal

Cable

matching problem 2 expression of implied facts29
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

Implied facts:

Rudder Control System

“The pilot presses the pedal.”

“The pedal pulls a cable.”

“The cable moves the rudder.”

agent

object

behavior

Pilot

Script

Rudder

agent

object

subevents

“The pilot moves the rudder using the pedal.”

Press

Pull

Move

object

agent

object

instr-

ument.

“The pedal moves the rudder using the cable.”

agent

Move

Pedal

Cable

object

instrument

agent

Move

slide30

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

status and assumptions
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
challenges
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.”
summary
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