A Parameterized Approach to Integrating Aspect with Lexical-Semanics for Machine Translation

This paper discusses how a two-level knowledge representation model for machine translation integrates aspectual information with lexical-semantic information by means of parameterization. The integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspectual realization processes that operate during the production of the target-language sentence: there are often a large number of lexical and aspectual possibilities to choose from in the production of a sentence from a lexical semantic representation. Aspectual information from the source-language sentence constrains the choice of target-language terms. In turn, the targetlanguage terms limit the possibilities for generation of aspect. Thus, there is a two-way communication channel between the two processes. This paper will show that the selection/realization processes may be parameterized so that they operate uniformly across more than one language and it will describe how the parameterbased approach is currently being used as the basis for extraction of aspectual information from corpora. I N T R O D U C T I O N This paper discusses how the two-level knowledge representation model for machine translation presented by Dorr (1991) integrates aspectual information with lexical-semantic information by means of parameterization. The parameter-based approach borrows certain ideas from previous work such as the lexical-semantic model of Jackendoff (1983, 1990) and models of aspectual representation including Bach (1986), Comrie (1976), Dowty (1979), Mourelatos (1981), Passonneau (1988), Pustejovsky (1988, 1989, 1991), and Vendler (1967). However, unlike previous work, the current approach examines aspectual considerations within the context of machine translation. More recently, Bennett *This paper describes research done in the Institute for Advanced Computer Studies at the University of Maryland. A special thanks goes to Terry Gaasterland and Ki Lee for helping to close the gap between properties of aspectual information and properties of lexical-semantic structure. In addition, useful guidance and commentary during this research were provided by Bruce Dawson, Michael Herweg, Jorge Lobo, Paola Merlo, Norbert Hornstein, Patrick SaintDizier, Clare Voss, and Amy Weinberg. (1) S y n t a c t i c : ( a ) N u l l S u b j e c t d i v e r g e n c e : E: I have seen M a r y 4. S: He vls to a M a r l s (Have seen ( to ) M a r y ) (b) C o n s t i t u e n t O r d e r d i v e r g e n c e , E: I have seen M a r y 4. G: Ich h a b e Mar ie gesehen ( I have Mar~" seen) (2) L e x i c e l S e m a n t i c : (a) Thematic divergence: E: I like M a r y 4. $: M a r l s me gusts a mf (Mary pleases me) (b) S t r u c t u r a l d i v e r g e n c e : E: John entered the house 4. S: J u a n entr6 en la cas& (John entered in the house) (c) C a t e s o r l a l d i v e r g e n c e : E: Yo ten~o h a m b r e 4* S: Ich h a b e Hun~er ( I have hun~er) (3) A e p e c t u a h (a) l te ra t i ve Divergence: E: John stabbed M a r y 4. S: J u a n le dio una puf laJada a M a r l s (John gave a knife-wound to M a r y ) S: J u a n le dio puf ia ladas a M a r l s (John gave knife-wounds to M a r y ) (b) D u r a t l v e D i v e r g e n c e , E: John m e t / k n e w M a r y 4* S: J u a n coaoc i6 a M a r l s ( J o h n m e t M a r y ) S: J u a n conoci£ a M&rfa (John knew Meri t ) Figure 1: Three Levels of MT Divergences et el. (1990) have examined aspect and verb semantics within the context of machine translation in the spirit of Moens and Steedman (1988). This paper borrows from, and extends, these ideas by demonstrating how this theoretical framework might be adapted for crosslinguistic applicability. The framework has been tested within the context of an interlingual machine translation system and is currently being used as the basis for extraction of aspectual information from corpora. The integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspectual realization processes that operate during the production of the target-language sentence: there are often a large number of lexical and aspectual possibilities to choose from in the production of a sentence from a lexical semantic representation. Aspectual information from the source-language sentence constrains the choice of target-language terms. In turn, the target-language terms limit the possibilities for generation of aspect. Thus, there is a two-way communication channel between the two processes. Figure 1 shows some of the types of parametric diver9ences (Dorr, 1990a) that can arise cross-linguistically.