The Process of Question Answering.

Abstract

Problems in computational question answering assume a new perspective when question answering is viewed as a problem in natural language processing. A theory of question answering has been proposed which relies on ideas in conceptual information processing and theories of human memory organization. This theory of question answering has been implemented in a computer program, QUALM, currently being used by two story understanding systems to complete a natural language processing system which reads stories and answers questions about what was read. The processes in QUALM are divided into 4 phases: (1) Conceptual categorization which guides subsequent processing by dictating which specific inference mechanisms and memory retrieval strategies should be invoked in the course of answering a question; (2) Inferential analysis which is responsible for understanding what the questioner really meant when a question should not be taken literally; (3) Content specification which determines how much of an answer should be returned in terms of detail and elaborations, and (4) Retrieval heuristics which do the actual digging to extract an answer from memory.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1977
Accession Number
ADA040559

Entities

People

  • Wendy G. Lehnert

Organizations

  • Yale University

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognition
  • Cognitive Science
  • Computer Programs
  • Computer Science
  • Computers
  • Databases
  • Human Behavior
  • Information Processing
  • Language
  • Mental Processes
  • Military Research
  • Natural Language Processing
  • Natural Languages
  • Personality
  • Psychology
  • Recognition

Readers

  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval