BBN: description of the PLUM system as used for MUC-5

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:• more rapid development of new applications,• the ability to train (and re-train) systems based on user markings of correct and incorrect output,• more accurate selection among interpretations when more than one is found, and• more robust partial interpretation when no complete interpretation can be found.

REFERENCES

• 1: Damaris Ayuso , Sean Boisen , Heidi Fox , Herb Gish , Robert Ingria , Ralph Weischedel, BBN: description of the PLUM system as used for MUC-4, Proceedings of the 4th conference on Message understanding, June 16-18, 1992, McLean, Virginia [doi>10.3115/1072064.1072091]
• 2: Lucja Iwańska , Douglas Appelt , Damaris Ayuso , Kathy Dahlgren , Bonnie Glover Stalls , Ralph Grishman , George Krupka , Christine Montgomery , Ellen Riloff, Computational aspects of discourse in the context of MUC-3, Proceedings of the 3rd conference on Message understanding, May 21-23, 1991, San Diego, California [doi>10.3115/1071958.1071998]
• 3: Tomoyoshi Matsukawa , Scott Miller , Ralph Weischedel, Example-based correction of word segmentation and part of speech labelling, Proceedings of the workshop on Human Language Technology, March 21-24, 1993, Princeton, New Jersey [doi>10.3115/1075671.1075724]
• 4: Ralph Weischedel , Damaris Ayuso , R. Bobrow , Sean Boisen , Robert Ingria , Jeff Palmucci, Partial parsing: a report on work in progress, Proceedings of the workshop on Speech and Natural Language, p.204-209, February 19-22, 1991, Pacific Grove, California [doi>10.3115/112405.112437]
• 5: Ralph Weischedel , Richard Schwartz , Jeff Palmucci , Marie Meteer , Lance Ramshaw, Coping with ambiguity and unknown words through probabilistic models, Computational Linguistics, v.19 n.2, June 1993