Model for Lexical Knowledge Base

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.