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Semi-automatic Fact Extraction and Organization of Persons in Genealogical Records Joseph Park Brigham Young University

Semi-automatic Fact Extraction and Organization of Persons in Genealogical Records

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Semi-automatic Fact Extraction and Organization of Persons in Genealogical Records. Joseph Park Brigham Young University. Fact Extraction. Extraction ontology Object identity resolution. Extraction Ontology. Recognizers. \b([1][6-9]\d\d)\b - PowerPoint PPT Presentation

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Page 1: Semi-automatic Fact Extraction and Organization of Persons in Genealogical Records

Semi-automatic Fact Extraction and Organization of Persons in Genealogical

RecordsJoseph Park

Brigham Young University

Page 2: Semi-automatic Fact Extraction and Organization of Persons in Genealogical Records

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Extraction ontology

Object identity resolution

Fact Extraction

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Extraction Ontology

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Recognizers

\b([1][6-9]\d\d)\b\b{Month}\.?\s*(1\d|2\d|30|31|\d)[.,]?\s*(\d\d\d\d)\b

Date recognizers

{Person}[.,]?.{0,50}\s*b[.,]?\s*{Birthdate}Person-Birthdate recognizer

{Son}[.,]?.{0,50}\s*[sS]on\s+of\s*.*?\s*{Person} Son-Person recognizer

{Person}[.,]?.{0,50};\s*m[.,]\s*{MarriageDate}[,]?\s*{Spouse} Person-Marriagedate-Spouse recognizer

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Example

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Canonicalization

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Object Identity

Resolution

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Schema mapping

Logic rules

Entity resolution

Fact Organization

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Schema Mapping

Extraction Ontology View of genealogist

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Example

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Example

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Morphology

Onomastics

Cultural pragmatics

Logic Rules

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Morphology

male female

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Onomastics

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Cultural Pragmatics

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Entity Resolution