A Schema & Constraint-Based Representation to Understanding Natural Language

This thesis attempts to represent the syntax and semantics of English sentences using a schema and constraint-based approach. In this approach, syntactic and semantic knowledge that are represented by schemata are processed in parallel with the utilization of network consistency techniques and an augmented version of Earley's context-free parsing algorithm. A sentence's syntax and semantics are disambiguated incrementally as the interpretation proceeds left to right, word by word. Each word and recognized grammatical constituent provide additional information that helps to guide the interpretation process. It is desirable to attempt to apply network consistency techniques and schema-knowledge representations on understanding natural language since the former has been proven to be quite efficient and the latter provides modularity in representing knowledge. In addition, this approach is appealing because it can cope with ambiguities in an efficient manner. Multiple interpretations are retained if ambiguity exists as indicated by the words processed so far. However, incorrect interpretations are eliminated as soon as their inappropriateness is discovered. Thus, backtracking search which is known to be inefficient is avoided.