Constructing a machine-tractable dictionary from longman dictionary of contemporary english

The research adopts a compositional-reduction approach to obtain a formalized set of definitions of sense entries in a nested predicate form, where the predicates are a set of "seed senses" and their utilization in the construction of the MTD.

Abstract

It is the purpose of this research to design a machine-tractable dictionary (henceforth MTD) from Longman Dictionary of Contemporary English (henceforth LDOCE). The MTD is intended to be a basic facility for a whole spectrum of natural language processing tasks. The research adopts a compositional-reduction approach to obtain a formalized set of definitions of sense entries in a nested predicate form, where the predicates are a set of senses. The focus of this research is on the derivation of these and their utilization in the construction of the MTD. The construction of the proposed MTD involves the following four steps: (1) Determine the of LDOCE, i.e., those word senses that are used in the definition of the meanings of 2,137 of LDOCE; (2) Derive the of LDOCE. The are a subset of the defining senses which are sufficient to define the set of defining senses of Step 1. The seed senses are taken as a natural set of semantic primitives derived from LDOCE; (3) Hand-code the initial knowledge base for the natural set of semantic primitives derived from LDOCE; (4) Construct a MTD for the controlled words and the rest of LDOCE words may means of bootstrapping from the initial hand-coded knowledge base. The bootstrapping process is a process of knowledge acquisition from dictionary definition text. Step 1 of the construction process has been completed. A total of 3,860 defining senses have been determined. Step 2 of the construction process has also been completed. A total of 3,280 word senses are found to be the seed senses of LDOCE. These seed senses are taken as a natural set of semantic primitives derived from the dictionary. The feasibility of Steps 3 and 4 of the construction process have been demonstrated with implemented examples. What remains to be accomplished is to complete Steps 3 and 4 to build a full-size MTD from LDOCE using as guidelines the results of initial implementation of the two steps.