Ontology-based Information Extraction with a Cognitive Agent Peter Lindes 1, Deryle Lonsdale, David...

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Ontology-based Information Extraction with a Cognitive Agent Peter Lindes 1 , Deryle Lonsdale, David Embley Brigham Young University AAAI 2015 1 Now at University of Michigan © 2015 Peter Lindes 1/22/2015 AAAI 2015 - IE with a Cognitive Agent 1

Transcript of Ontology-based Information Extraction with a Cognitive Agent Peter Lindes 1, Deryle Lonsdale, David...

Page 1: Ontology-based Information Extraction with a Cognitive Agent Peter Lindes 1, Deryle Lonsdale, David Embley Brigham Young University AAAI 2015 1 Now at.

AAAI 2015 - IE with a Cognitive Agent 1

Ontology-based Information Extraction with a Cognitive Agent

Peter Lindes1, Deryle Lonsdale, David EmbleyBrigham Young University

AAAI 2015

1Now at University of Michigan

© 2015 Peter Lindes

1/22/2015

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The Problem

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Goals and Strategies• OntoSoar project goals

– Extract genealogy facts from family history books– Project extracted information onto a conceptual model to

populate a searchable database• Strategies

– Use ideas from Embodied Construction Grammar– Use the Soar cognitive architecture– Integrate several levels of knowledge

• Long term goals– Build computational models of human language processing– Apply these models to real-world applications

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Example 1

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A Simple Ontology

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Charles Christopher Lathrop

has

18651817

born on died on

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Example2

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A More Complex Ontology

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Myra Harwood

Jonathan Squires

J. Wilbur Squires

Feb. 13, 1874

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The Solution

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Thus, intelligence is the ability to bring to bear all the knowledge that one has in service of one’s goals.

Newell (1990), p. 90

Page Layout *Text Analysis

SyntaxSemanticsPragmatics

World KnowledgeConceptual Models

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OntoSoar Architecture

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PDF Tools PopulatedUser

Ontology(OSMX)

Segmenter LG Parser Meaning Builder

Conceptual Semantic Analyzer

Mapper

Segment Rules(37)

Link Grammar

Grammar Constructions

(16)

Inference Rules

Text Segments Linkages Meaning Schemas

Knowledge Structures Facts

User Ontology (OSMX)

Soar

OntoESTool Set

(A total of 260 Soar productions)

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Construction Grammar

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REF-EXPR LE-VERB DATE

LIFE-EVENT

DateDateLifeEventLifeEventPersonPerson

REF-EXPR

SON-OF

PersonPersonSonOfSonOfPersonPerson

REF-EXPRson of

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Applying Constructions

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Charles Christopher Lathrop, N. Y. City, b. 1817, d. 1865, son of Mary Ely and Gerard Lathrop ;

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… More Constructions

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Charles Christopher Lathrop, N. Y. City, b. 1817, d. 1865, son of Mary Ely and Gerard Lathrop ;

Name

Person

Name

Person

Name

Person

SonOf

SonOf

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Building Knowledge

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Charles Christopher Lathrop, N. Y. City, b. 1817, d. 1865, son of Mary Ely and Gerard Lathrop ;

Person gender: M name: K͞Gerard Lathrop L͞ birth: death:

Person gender: M name: K͞Charles C. Lathrop L͞ birth: K͞1817 L͞ death: K͞1865 L͞

Person gender: F name: K͞Mary Ely L͞ birth: death:

Couplemarried:

wifehusband

child parents

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Knowledge Structures Compared

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… his widow married JONATHAN SQUIRES, who was born in Ohio, July 25, 1823, by whom she had one son, J. Wilbur, born June 16, 1865,

Charles Christopher Lathrop, N. Y. City, b. 1817, d. 1865, son of Mary Ely and Gerard Lathrop ;

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Results on Examples

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CCL Myra OD1 OD2 OD3 OD4 OD5 OD6 OD7 OD8 OD9 OD10 OD11 OD120

20

40

60

80

100

120

Data Accuracy for Test Data

Persons Births and Deaths Marriages Children

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Results on The Ely Ancestry

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Item Type Instance Found

Persons 16,848

Births 8,609

Deaths 2,406

Genders 1,674

Couples 3,343

Children 3,049

Total 35,929

a book of 830 pages, including our Example 1

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Conclusions

Contributions• Produces usable genealogy

data from scanned books• Does this using:

– Integration of several levels of knowledge

– An adaptation of Embodied Construction Grammar

– A cognitive architecture (Soar)

Future Work• Integrate parsing with

semantics• Develop a means to learn

many new constructions• Adapt to varying book styles• Scale up to perform well on

100’s of thousands of books

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It works! … and, it could work a lot better.