Asymmetry in Parsing and Generating with Unification Grammars: Case Studies From ELU

Asymmetry in Parsing and Generating with Unification Grammars: Case Studies From ELU Graham Russell,* Susan Warwick,* and John Carroll? * ISSCO, 54 rte. des Acacias ? Cambridge University Computer Laboratory 1227 Geneva, Switzerland New Museums Site, Pembroke Street russell@divmm.onige.ch Cambridge CB2 3QG Abstract Recent developments in generation algorithms have enabled work in nnificafion-based computational linguistics to approach more closely the ideal of grammars as declarative statements of linguistic facts, neutral between analysis an0_ synthesis, x-"~-oui this perspective, however, the situation is still far from perfect; all known methods of generation impose constraints on the grammars they assume. We briefly consider a number of proposals for generation, outlining their consequences for the form of grammacs, and then report on experience arising from the addition of a generator to an exist- ing unification environment. The algorithm in question (based on that of Shieber et al. (1989)), though among the most permissive currently avail- able, excludes certain classes of parsable analyses. 1. Introduction Parsing and generation me both concerned with the relation between texts and representations, and in so far as a grammar defines this relation without reference to direction, it may be regarded as rever- sible. Yet, in practice, the program which 'applies' a grammar for the purpose of parsing is quite dis- tinct from the one which performs generation.t The essential difference between parsing and generating lies in the nature of the input. The text, as a string of words, traditionally establishes the starting point of parsing; whether the processing is top-down or bottom-up, the basis for selecting grammar roles is information associated with words in the lexicon. In the case of generation, there is in general no guarantee that the constituents of an input representation correspond to words; a portion of the input may be related directly to a given word, or it may be the result of combining representations associated to some sequence of rules, portions of which me ultimately related to lexical items. For example, if the sentence John kicked the bucket receives the semantic representation die(John), it is i Parsing and generation need not employ dif- ferent algorithms or control strategies; see Shieber (1988) for discussion. However, a truly reversible gram would be an entirely different undergoking what is described here. One such project is currently under way at New Mexico State Universi- ty (Yorick Wilk~, p.c.). 205 relatively easy to see how during parsing the recog- uilion of kicked and the bucket will provide the necessary information (from the lexical entry for kick) to build that represemo~on. "l'ne representa- tion and the lexical items are in general related not dhectly, but rather via intennediate syntactic rules, any of which is able to manipulate the representa- tion in arbitrary ways; in generation, it is not possi- ble to identify the correct lexical item without con- sidering the syntactic rules which may intervene. The generation problem, then, consists in how to build a syntactic structure faom an initial representation, taking it as the root, and extending the structure …

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