Achieving Bidirectionality

Achieving Bidirectionality Paul S. Jacobs Artificial Intelligence Program GE Research and Development Cenl;er Schenectady, NY 12301 USA Abstract The topic of BIDIltECT1ONAL1TY~ using common knowledge in language processing for both anMysis and generation, is of both practical and theoretical concern. Theoretically, it is important to determine what knowledge structures can be applied to both. Practically, it is important that a cmn- petent natural language system be ~ble to generate out- puts tilat are relevant to the inputs it understands, with- out exce~:sive redundancy. Tiffs problem revolves around the ~bility to relate linguistic structures declaratively to their mc~ming. 1 Introduction BIDIRECTIONALITY, or the ability to use a cormnon knowledge base for both language anMysis mid generation, is a desirable feature of a reM language proccssing system. A natural lan- guage "front end" must not only perform syntactic anMysis, but must derive a suitable representation of a meaning or in- tention from a linguistic input. A natural language generator performs the: inverse task of producing a linguistic utterance fi'om a nmm~ing or intention. A bidirectional system performs both tusks using as much shaxed knowledge as possible. Two praeticM concerns motivate this work: (1) A system that uses shax'ed knowledge for analysis and generation will produce output ix* the subset of laa.lgu~ge that it understands, thus avoiding inconsistences between the input and output, and (2) Using shared knowledge avoids the inefficiency of having distinct encodings of the same linguistic information. The first concern, having a naturM language interface "speak" the same language it understands, is more than a con- veniencc. Responses in a dialogue often use a word or phrase that has been mentioned by another speaker. This cannot be done effectively unless the word or phrase is common to both the input and output language. A computer user will expect the system to understand a phrase or construct that the sys- tem has itsel[ used; this aggravates the consequences of incon- sistencies between input and output language. Moreover, if an interface is to be traalsportable across domains, a distinct subset of language will be applicable to each domain. The bidi- rectional knowledge base allows both the input and output to be constrained simultaneously. The second concern, efficiency of knowledge representa- tion, becomes more compelling as the lexical and semantic ca- pabilities of natural language systems increase. While there is ample motivatioz, for having a common grammar fox" anal- ysis and ge:oeration, the need for a common lexicon is even stronger. H~ving two lexicons is counterintuitive; what makes practical sense is to have a single lexicon indexed differently for gene.ration fl'om analysis. Now that many systems have more mid more knowledge built into their lexicons, the effects of redundancy become more &'astie. When more information is required of the lexicon, however, the difficulties in developing a shared lexicon are more pronounced. The principal concern in designing a natural hmguage sys- tem that performs both analysis and generation, thereibre, is a bidirectional lexicon. The main issue to be eonsidered here is wt,at information nmst …

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