MUC-3 Test Results and Analysis
Christine A. Montgomery, Bonnie Glover Stalls, Robert S. Belvin, Naicong Li, Robert S. Belvin, Alfredo Arnaiz, Susan B. Hirsh · 1991
LSI's overall natural language processing (NLP) objective is the development of a broad coverage, reusable sys-tem which is readily transportable to additional domains, applications, and sublanguages in English, as well as providing a foundation for our multilingual work. Our system, called DBG, for Data Base Generator, is comprised of a set of NLP components which have been developed, extended, and rebuilt over a period of some years. The core of the system is an innovative Principle-based parser, using ideas from [1], which we began developing in the course of MUC-3 to replace our previous chart parser. Our approach thus relies on the con-cept of powerful, robust parsing as the most crucial component in an NLP system. In applying our NLP system to text extraction, our ultimate objective is to develop a high quality text extraction system, where "high quality " is defined as scoring above 80 %-- a number well beyond any current MUC scores. In line with these NLP objectives, our major focus for MUC-4 was a follow-up to our main "lesson learned " i n MUC-3, which was to acquire a machine-readable dictionary (MRD) and integrate its content into the DBG sys-tem. When attempts to acquire the computer-friendly Longmans or one of the Oxford Dictionaries were unsuc-cessful, we turned to ACL's CD-ROM containing the Collins English Dictionary. The most correct version of the CED on the ACL CD-ROM was apparently developed directly from a medium prepared for the typographer, and unfortunately lacks any documentation of features, fonts, language, etc. The effort of acquiring an d