17 Dec 2007AFOSR MURI Meeting1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford...

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17 Dec 2007 AFOSR MURI Meeting 1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford Professor of Artificial Intelligence and Computer Science

Transcript of 17 Dec 2007AFOSR MURI Meeting1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford...

Page 1: 17 Dec 2007AFOSR MURI Meeting1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford Professor of Artificial Intelligence and Computer Science.

17 Dec 2007 AFOSR MURI Meeting 1

Collecting Grist for the Analogical Mill

Patrick H. Winston

Ford Professor of Artificial Intelligence and Computer Science

Page 2: 17 Dec 2007AFOSR MURI Meeting1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford Professor of Artificial Intelligence and Computer Science.

17 Dec 2007 AFOSR MURI Meeting 2

Cultural Prediction & Blunder Stopping

• Stories capture cultural beliefs & values• Folktales, Myths, Morality Tales, Religious Texts, Urban

Legends

• Analogical Framework• Predict role-models; individual & group behavior

across cultures from stories

• Story Database• A bottleneck

Experimenter

Automatic NLP

Structured Representations

Textual Materials

Page 3: 17 Dec 2007AFOSR MURI Meeting1 Collecting Grist for the Analogical Mill Patrick H. Winston Ford Professor of Artificial Intelligence and Computer Science.

17 Dec 2007 AFOSR MURI Meeting 3

The Story Workbench• Modular

• Easily Extendible

• Cross-Platform (99% pure Java)

• Open Source

• Large, dedicated User-base

• Commercial-Quality

1. User enters Natural Language

2. Workbench makes its

best guess

3. Problems are highlighted

4. User enters corrections or adds detail

Workflow

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17 Dec 2007 AFOSR MURI Meeting 4

A Rich Suite of Representations

• Context(last game of the World Series)

• Location(pitcher is on the mound, baseman and crowd are in front of the pitcher)

• Events (and their order)(The look, the windup, then the pitch)

• Causality(pitcher’s pitch causes the ball to fly forward)

• Discourse(pitcher is rumored to have taken steroids, he’s quoted as denying it)

• Emotions(The pitcher is calm, the crowd is going wild)

• Motivations(The pitcher wants to win the game, wants to strike out this batter)

pitch

pitcherball

batter

(to)

Classical

Where we are goingListening on the Radio to:

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17 Dec 2007 AFOSR MURI Meeting 5

Accomplishments to Date

• Implemented Story Workbench foundation• Syntax-level NLP representations & parsers

• Facility for user correction

• Interfaced successfully with Forbus Group• Ability to assign CYC propositions to text (semantic interpretation)

• Started beta testing• Word Sense Disambiguation as a benchmark semantic annotation task

• Annotation of Discourse structure by Gibson & Kraemer at MIT BCS

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Activities in the Near-term

• Implement next layers of representation and parsers• Entities• Events• Discourse Relations• Mental States and Motivations• Moral of the Story

• Collaborate with Medin at Northwestern to infer beliefs from stories and predict Menominee and Itza behavior