BBN's PLUM Probabilistic Language Understanding System
Abstract
Traditional approaches to the problem of extracting data from texts have emphasized hand-crafted linguistic knowledge In contrast, BBN's PLUM system (Probabilistic Language Understanding Model) was developed as part of an ARPA-funded research effort on integrating probabilistic language models with more traditional linguistic techniques. Our research and development goals are: * Achieving high performance in objective evaluations, such as the Tipster evaluations. * Reducing human effort in porting the natural language algorithms to new domains and to new languages. * Providing technology that is scalable to realistic applications. We began this research agenda approximately three years ago. During the past two years, we have ported our data extraction system (PLUM) to a new language (Japanese) and to two new domains.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1993
- Accession Number
- ADA460668
Entities
People
- Constantine Papageorgiou
- Damaris Ayuso
- Dawn Maclaughlin
- Heidi Fox
- Hiroto Hosihi
- June Abe
- Masaichiro Kitawa
- Ralph Weischedel
- Scott R. Miller
- Sean Boisen
- Tomoyoshi Matsukawa
- Tsutomu Saki
- Yoichi Miyamoto
Organizations
- BBN Technologies