The ECO family

This paper presents an overview of the ECO (English COnversational System) family formalism of semantic network. In the paper, we describe the components of our semantic network, discussing its suitability as a representation of propositional knowledge. The use of our semantic network as a uniform representation mediating between specialised representations appropriate to particular task domains (e.g., understanding natural languages, etc.) is discussed. We motivate and explain a comprehensive network formalism. Special problems with respect to the use of logical connectives, quantifiers, descriptions, modalities, and certain other constructions that fail in conventional semantic networks, are systematically resolved with extensions to conventional network notations. The representation harmonizes with linear one-dimensional logical notations, illustrating the close kinship of the two notations. This kinship supports the claim that networks have inherited formal interpretability from logical notations. Several issues of network form and content, which are more fundamental than the choice of a network syntax, are addressed. These issues are: (i) primitive versus nonprimitive representations; (ii) the separation of propositional content of text from pragmatic aspects; and (iii) network normal form versus ad hoc systems. The design of computer systems for specific tasks depends in part on early commitments to these issues. The succinctness, clarity, and intuitive nature of semantic networks argues in their favour if only for purely methodological advantages. Semantic networks are readable; they suggest procedures for comprehension and inference, and the computer data structures which they resemble. Examples will demonstrate how associative processing algorithms and complex pattern matching operations are readily identifiable using networks. These examples are given in the context of natural language understanding utilizing networks in a state-based conceptual representation. We discuss how to superimpose organisational strategies into the network representations, beginning with the representation of lexical information and extending to the superimposition of topical organisations in the knowledge base. Several special purpose inference mechanisms extend the topical organisation we superimpose on concepts to aid retrieval of other types of information about concepts. The use of networks is assessed and promising areas for future research are described.