Deductive Question Answering from Multiple Resources

Citation

Waldinger, R. and Appelt, D. E. and Fry, J. and Israel, D. J. and Jarvis, P. and Martin, D. and Riehemann, S. and Stickel, M. E. and Tyson, M. and Hobbs, J. and Dungan, J. L. Deductive Question Answering from Multiple Resourcesin New Directions in Question Answering, AAAI, 2004.

Abstract

Questions in natural language are answered by consulting multiple sources and inferring answers from information they provide. An automated deduction system, equipped with an axiomatic application-domain theory, serves as the coordinator for the process. Sources include data bases, Web pages, programs, and unstructured text. Answers may contain text or visualizations. Although the approach is domain-independent, many of our experiments have dealt with geographic questions.


Read more from SRI

  • An arid, rural Nevada landscape

    Can AI help us find valuable minerals?

    SRI’s machine learning-based geospatial analytics platform, already adopted by the USGS, is poised to make waves in the mining industry.

  • Two students in a computer lab

    Building a lab-to-market pipeline for education

    The SRI-led LEARN Network demonstrates how we can get the best evidence-based educational programs to classrooms and students.

  • Code reflected in a man's eyeglasses

    LLM risks from A to Z

    A new paper from SRI and Brazil’s Instituto Eldorado delivers a comprehensive update on the security risks to large language models.