building a system that can learn by reading

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Building a System that canLearn by Reading

Kevin LivingstonPhD Candidate

Cognitive Systems DivisionEECS Department

Northwestern University

Presented at University of Dayton November 3, 2006As part of the Computer Science Research Colloquium Series

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Understanding Systems

Knowledge Base

Text

Text Understanding

System QuestionAnswering

Explanation

Reasoning

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Examples of Intelligent Systems

• Digital Assistants

• Conversational Agents– Imagine a video game character that actually

talked to you

• Intelligent Games

• Search

• Question Answering

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Modeling and Using Knowledge

• Frames (Minsky)

• Scripts (Shank)

• Qualitative Reasoning (Forbus)

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Semantic Memory

• Ontology– Doctors are people– Bombings are events

• Semantics– Doctors have patients– Bombings have targets

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Episodic Memory

• Memory Instances– Madrid is a city– Madrid is in Spain– The Madrid Bombings is a terrorist attack– The Madrid Bombings occurred on March 11,

2004– Al Qaida is a terrorist organization

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Modeling Reasoning

• Logic Based Systems– Cyc (Cycorp; Austin, TX)– Fire (Qualitative Reasoning Group (QRG);

Northwestern)

• Statistical• Bayesian• Markovian• Neural Nets

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Knowledge Bases

Knowledge Base

Text

Text Understanding

System QuestionAnswering

Explanation

Reasoning

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Available Knowledge Bases• Information Retrieval (IR) techniques

– mine information from Internet (MUC and TREC)

• Open Mind Common Sense (OMCS)– Sentences collected from Internet contributors– Mined for knowledge

• Knowledge Machine (KM)– Frame based

• ResearchCyc– Latest release ~3,000,000 assertions– Predicate Logic in CycL

• First order and some second order constructs

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ResearchCyc

• Bombings are Attacks and Attacks are Events(genls Bombing AttackOnObject)

(genls AttackOnObject Event)

• The Madrid terrorist attack was a bombing(isa

TerroristAttack-September-8-2003-Madrid

Bombing)

• Al Qaida is an Islamist Terrorist Group(isa AlQaida TerroristGroup-Islamist)

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ResearchCyc (cont.)

• Location of an event

(eventOccursAt


CityOfMadridSpain) • Perpetrator of an event(perpetrator


AlQaida)

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ResearchCyc (cont.)

• Person being killed(organismKilled SpaceShuttleChallengerDisaster ChristaMcAuliffe)

• Deaths caused by an attack(deathToll


Person190)

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Building Knowledge Bases

• Slow and Tedious– years to grow Cyc from 1.2M to 3M assertions

• Requires Training– measured in weeks+, for GUI tools (SHAKEN)

• Expensive– Project Halo estimates $10,000 per page!

of AP level Chemistry content

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Available Information

• Encyclopedias

• Newspapers

• Online sources

• Print

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A Better Way?Teach the Computer to Read

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What we want to Read

• Episodic Knowledge– New people– New events

• General Knowledge– “the heart is a pump”

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Standard Model forNatural Language Processing

Dictionary

Text

POSTagging

Grammar

SyntacticParser

SemanticInterpreter

Semantics

Tagged Text

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“Time flies like an arrow.”

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“Time flies like an arrow.”• Time moves quickly just like an arrow does

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• (You should) time flies like you would an arrow

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• Time flies in the same way that an arrow would (time them)

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• Time those flies that are like arrows;

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• Time those flies that are like arrows;

• A type of flying insect, "time-flies," enjoy arrows (compare Fruit flies like a banana.)

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Picture ofGeorge Burns

AndGrace Allen

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Grace,Those are beautiful flowers.


AndGrace Allen

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Grace,Those are beautiful flowers.

Where did they come

from?


AndGrace Allen

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Don’t you remember, George?


AndGrace Allen

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AndGrace Allen

You said that if I went to visit Clara Bagley

in the hospital I should be sure to take her flowers.

So when she wasn’t looking,

I did.

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AndGrace Allen

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Common Sense

• “You said that if I went to visit Clara Bagley in the hospital I should be sure to take her flowers. So, when she wasn't looking, I did.”

– take flowers from her– take flowers to her

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Picture ofElevatorOperator

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Down?


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ThatWay!


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Context in the Environment

“Down?”

What does the question mean?– Which way is down?– Are you going down?

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Language UnderstandingGoals include understanding:

– The meaning of the text– How it fits into what is known– The purpose of being told

Requires:– Common sense knowledge– Awareness of context

Our model is to get to knowledge as quickly as possible, with as few intermediate steps as possible.

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Reader ExampleAn attack occurred in MadridThe bombing killed 190 peopleThe bombing was perpetrated by Al-Qaida

(eventOccursAt TerroristAttack-September-8-2003-Madrid CityOfMadridSpain)(perpetrator TerroristAttack-September-8-2003-Madrid AlQaida)(deathToll TerroristAttack-September-8-2003-Madrid Person 190)(isa TerroristAttack-September-8-2003-Madrid Bombing)

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Lexical Processing

“An attack occurred in Madrid.”• “attack”(singular Attack-TheWord “attack”)(denotation Attack-TheWord CountNoun 0

AttackOnObject)(isa ?x AttackOnObject)

• “Madrid”(placeName-Standard CityOfMadridSpain

"Madrid")(isa CityOfMadridSpain City)

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Rule Pattern

• Pattern:(isa ?event Event)

Occur-TheWord

In-TheWord

(isa ?location GeographicLocation)

• Results:(eventOccursAt ?event ?

location)

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Pattern Matching• Pattern:

(isa ?event Event) Occur-TheWordIn-TheWord (isa ?location GeographicLocation)

• Input:– “An”– “attack” (isa ?x AttackOnObject)

– “occurred” Occur-TheWord

– “in” In-TheWord– “Madrid” (isa CityOfMadridSpain City)

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Rule Completion“An attack occurred in Madrid.”• Pattern:

(isa ?event Event) Occur-TheWordIn-TheWord (isa ?location GeographicLocation)

• Results:(eventOccursAt ?event ?location)

• Constraints:(isa ?event AttackOnObject)

• Bindings from Reading:((?location . CityOfMadridSpain))

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Remindings“An attack occurred in Madrid.”• Pattern: (isa ?event Event)

Occur-TheWordIn-TheWord (isa ?location GeographicLocation)

• Results:(eventOccursAt ?event ?location)

• Constraints:(isa ?event AttackOnObject)

• Bindings from Reading:((?location . CityOfMadridSpain))

• Remindings from Memory:((?event . TerrorAttack-Sept8-2003-Madrid))

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Coreference ResolutionAn attack occurred in Madrid. The bombing was

perpetrated by Al-Qaida.

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Coreference ResolutionAn attack occurred in Madrid

Results: (eventOccursAt?event?location)

Constraints:(isa ?event AttackOnObject)

Bindings from Reading:((?location .

CityOfMadridSpain))Remindings from Memory:((?event . TerrorAttack-

Sept8-2003-Madrid))

The bombing was perpetrated by Al-Qaida

Results: (perpetrator?action

?agent)

Constraints:(isa ?action Bombing)

Bindings from Reading:((?agent . AlQaida))

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Sept8-2003-Madrid))



?agent)



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Sept8-2003-Madrid))



?agent)



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Sept8-2003-Madrid))



?agent)



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Sept8-2003-Madrid))



?agent)



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Coreference

• Refer to a more general or specific type– “bombing” and “attack”

• Consistent with being the same,

have a known shared instance in memory– “doctor” and “father of four”

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Tracking Ambiguity

• Words are ambiguous– “Bush”

• A shrubbery?• A president? Which one?

• Sentences and Phrases– “take her flowers”– “Iraq borders Iran on the North.”

• Intension– “Down?”– “Where is Baghdad?”

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% of sentences processed under time

0

10

20

30

40

50

60

70

80

90

100

1 10 100 1000 10000 100000 1E+06 1E+07

time (ms)

% o

f co

rpu

s se

nte

nce

s p

roce

ssed

RDE

SLE

WLE

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What Learning Reader can Read

• Information about existing instances– “the 2003 Madrid bombing”

• Information extending existing instances– “the attack killed 190 people”

• Information representing new instances– “An attack occurred in Al Anbar.”

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What Learning Reader can’t Read

• Larger patterns– Scripts: “A bomb went off.”

“6 people were arrested.”

• Generalizations“All countries have political leaders.”

“The heart is a pump.”

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Dr. Christopher K. RiesbeckDr. Ken ForbusDr. Larry BirnbaumAbhishek Sharma

Dr. Jennifer SeitzerDr. Saverio Perugini

grant HR0011-04-1-0051

Acknowledgements

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For more Information

http://cs.northwestern.edu/~livingston/http://cs.northwestern.edu/~livingston/talks.html

Kevin LivingstonPhD Candidate

Cognitive Systems DivisionEECS Department

Northwestern University

building a system that can learn by reading

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