Download - 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


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


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


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:


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


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