Faust: Flexible Acquistion and Understanding System for Text

Abstract

The vast majority of scientific and technical knowledge is expressed in natural-language (NL) texts. Our objective was to create an automated reading system that makes the knowledge in NL texts accessible to any of an open-ended range of formal reasoning systems. Our approach was based on large-scale statistical (probabilistic) joint inference over relational models. This vision involved a radical re-thinking of the architecture for Machine Reading systems.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2013
Accession Number
ADA588330

Entities

People

  • Andrew McCallum
  • Christopher Manning
  • Christopher Ré
  • Daniel Jurafsky
  • Daniel S. Weld
  • David E. Wilkins
  • David Israel
  • Jude Shavlik
  • L. L. Voss
  • Pedro Domingos

Organizations

  • SRI International

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence Software
  • Automata Theory
  • Bayesian Networks
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Mining
  • Databases
  • Information Processing
  • Information Science
  • Monte Carlo Method
  • Natural Language Processing
  • Ontologies
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computational Linguistics
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation