Growing Semantic Grammars

Growing Semantic Grammars Marsal Gavaldh and Alex Waibel Interactive Systems Laboratories Carnegie Mellon University Pittsburgh, PA 15213, U.S.A. marsal@cs, cmu. edu Abstract A critical path in the development of natural language understanding (NLU) modules lles in the difficulty of defining a mapping from words to semantics: Usually it takes in the order of years of highly-skilled labor to de- velop a semmltic mapping, e.g., in the form of a semantic grammar, that is comprehensive enough for a given do- main. Yet, due to the very nature of human language, such mappings invariably fail to achieve full coverage oil unseen data. Acknowledging the impossibility of stat- ing a priori all the surface forms by which a concept can be expressed, we present GSG: an empathic computer system for the rapid deployment of NLU front-ends and their dynamic customization by non-expert end-users. Given a new domain for which an NLU front-end is to be developed, two stages are involved. In the author- ing stage, GSG aids the developer in the construction of a simple domain model and a kernel analysis gram- mar. Then, in the run-time stage, GSG provides the end- user with an interactive environment in which the kernel grammar is dynamically extended. Three lear~ling meth- ods are employed in the acquisition of semantic mappings from mmeen data: (i) parser predictions, (ii) tfidden un- derstanding model, and (iii) end-user paraphr~es. A baseline version of GSG has been implemented and pre- liminary experiments show promising results. 1 Introduction The mapping between words and semantics, be it in the form of a semantic grammar, 1 or of a set of rules that transform syntax trees onto, say, a frame-slot structure, is one of the major bottlenecks in the de- velopment of natural language understanding (NLU) systems. A parser will work for any domain but the semantic mapping is domain-dependent. Even after the domain model has been established, the daunting task of trying to come up with all the possible surface forms by which each concept can 1 Semantic grammars are grammars whose non-terminals correspond to semantic concepts (e.g., [greeting] or [suggest_time]) rather than to syntactic constituents (such as Verb or IounPhrass). They have the advantage that the semantics of a sentence can be directly read off its parse tree, and the disadvantage that a new grammar must be developed for each domain. be expressed, still lies ahead. Writing such map- pings takes in the order of years, can only be per- formed by qualified humans (usually computational linguists) and yet the final result is often fragile and non-adaptive. Following a radically different philosophy, we pro- pose rapid (in the order of days) deployment of NLU modules for new domains with on-need basis learn- ing: let the semantic grammar grow automatically when and where it is needed. 2 Grammar development If we analyze the traditional method of developing a semantic grammar for a new domain, we find that the following stages are involved. 1. Data collection. Naturally-occurring data from the domain at hand are …

Content truncated to 500 words