Model for Lexical Knowledge Base

Model for Lexical Knowledge 13ase Michio Isoda, Hideo Also Keio University, Faculty of Science and Technology Noriyuki Kamibayashi and Yoshifnmi Matsunaga Fuji Xerox Co. Ltd., System Technology Laboratory Abstract This paper describes a model for a lexical knowledge base (LKB). An LKB is a knowledge base management system (KBMS) which stores various kinds of dictionary knowledge in a uniform framework and provides multiple viewpoints to the stored knowledge. KBMSs for natural language knowledge will be fundamental components of knowledgeable environments where non-computer professionals can use various kinds of support tools for document preparation or translation. However, basic models for such KBMSs have not been established yet. Thus, we propose a model for an LKB focusing on dictionary knowledge such as that obtained from machine-readable dictionaries. When an LKB is given a key from a user, it accesses the stored knowledge associated with that key. In addition to conventional direct retrieval, the LKB has a more intelligent access capability to retrieve related knowledge through relationships among knowledge units. To represent complex and irregular relationships, we employ the notion of implicit relationships. In contrast to conventional database models where relationships between data items are statically defined at data generation time, the LKB extracts relationships dynamically by interpreting the contents of stored knowledge at run time. This makes the LKB more flexible; users can add new functions or new knowledge incrementally at any time. The LKB also has the capability to define and construct new virtual dictionaries from existing dictionaries. Thus users can define their own customized dictionaries suitable for their specific purposes. The proposed model provides a logical foundation for building flexible and intelligent LKBs. 1. Introduction Computers have been powerful support tools for various kinds of human activities. In particular, high performance personal workstations provide convenient and friendly environments for office workers and engineers. Conventional systems, however, provide only basic support tools such as text editors, text formatters, spelling checkers, and mail handlers. With the progress in natural language processing, database management, and user- machine interface techniques, more advanced support tools have emerged. They include machine translation systems, style analyzers, personal databases, an electronic book [Weyer82], and an electronic encyclopedia [Weyer85]. Currently, these systems are in the experimental stage and are being implemented and used individually. They will eventually be integrated to build knowledgeable environments in which non-computer professionals can perform their tasks more quickly and easily. The fundamental components of these tools are large knowledge bases which store knowledge about natural languages and application areas. Since many application programs will share the same kind of knowledge, these knowledge bases must be application-independent components that can be accessed from application programs through some predefined interfaces. Thus, it is importmnt to establish methodologies to construct these knowledge bases [Amsler84, Calzorali84a]. The methodologies include basic models, architectures, knowledge representation schemes, and implementation techniques. Since knowledge representation schemes and their usage vary widely, it is difficult to build a general knowledge base capable of coping with all applications described above. Thus, as a first …

Content truncated to 500 words