Responding to Semantically Ill-Formed Input

RESPONDING TO SEMANTICALLY ILL-FORMED INPUT Ralph Grishman and Ping Peng Computer Science Department New York University 251 Mercer Street New York, NY 10012 Abstract One cause of failure in natural language in- terfaces is semantic overshoot; this is re- flected in input sentences which do not cor- respond to any semantic pattern in the sys- tem. We describe a system which provides helpful feedback in such cases by identifying the "semantically closest" inputs which the system would be able to understand. 1. Introduction Natural language interfaces have achieved a lim- ited success in small, well circumscribed domains, such as query systems for simple data bases. One task in constructing such an interface is identi- fying the relationships which exist in a domain, and the possible linguistic expressions of these re- lationships. As we set our sights on more complex domains, it will become much harder to develop a complete or nearly complete catalog of the rele- vant relationships and linguistic expressions; sub- stantial gaps will be inevitable. In consequence, many inputs will be rejected because they fail to match the semantic/linguistic model we have con- structed for the domain. We are concerned with the following question: what response should we give a user when his in- put cannot be analyzed for the reasons just de- scribed? The response "please rephrase" gives the user no clue as to how to rephrase. This leads to the well-known "stonewalling" phenomenon, where a user tries repeatedly, without success, to rephrase his request in a form the system will un- derstand. This may seem amusing to the outside observer, but it can be terribly frustrating to the user, and to the system designer watching his sys- tem being used. We propose instead to provide the user with sentences which are semantically close to the orig- inal input (in a sense to be defined below) and are acceptable inputs to the system. Such feed- back may occasionally be confusing, but we ex- pect that more often it will be helpful in showing the system's capabilities and suggesting possible rephrasings. In the remainder of this paper we briefly review the prior work on responding to ill- formedness, describe our proposal and its imple- mentation as part of a small question-answering system, and relate our initial experiences with this system. 2. Background A. Relative and Absolute Ill-form- edness Weischedel and Sondheimer (~,Veischedel, 1983) have distinguished two types of ill-formedness: ab- solute ill-formedness and relative ill-formedness. Roughly speaking, an absolutely ill-formed input is one which does not conform to the syntactic and semantic constraints of the natural language or the sublanguage; a relatively ill-formed input is one which is outside the coverage of a particular natural language interface. Our concern is pri- marily with relative ill-formedness. For complex domains, we believe that it will be difficult to cre- ate complete semantic models, and therefore that relatively ill-formed input will be a serious prob- lem - a problem that it will be hard for users to remedy without suitable feedback. …

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