A DOP Model for Semantic Interpretation

A DOP Model for Semantic Interpretation* Remko Bonnema, Rens Bod and Remko Scha Institute for Logic, Language and Computation University of Amsterdam Spuistraat 134, 1012 VB Amsterdam Bonnema~mars. let. uva. nl Rens. Bod@let. uva. nl Remko. Scha@let. uva. nl Abstract In data-oriented language processing, an annotated language corpus is used as a stochastic grammar. The most probable analysis of a new sentence is constructed by combining fragments from the corpus in the most probable way. This approach has been successfully used for syntactic anal- ysis, using corpora with syntactic annota- tions such as the Penn Tree-bank. If a cor- pus with semantically annotated sentences is used, the same approach can also gen- erate the most probable semantic interpre- tation of an input sentence. The present paper explains this semantic interpretation method. A data-oriented semantic inter- pretation algorithm was tested on two se- mantically annotated corpora: the English ATIS corpus and the Dutch OVIS corpus. Experiments show an increase in seman- tic accuracy if larger corpus-fragments are taken into consideration. 1 Introduction Data-oriented models of language processing em- body the assumption that human language per- ception and production works with representations of concrete past language experiences, rather than with abstract grammar rules. Such models therefore maintain large corpora of linguistic representations of previously occurring utterances. When processing a new input utterance, analyses of this utterance are constructed by combining fragments from the cor- pus; the occurrence-frequencies of the fragments are used to estimate which analysis is the most probable one. * This work was partially supported by NWO, the Netherlands Organization for Scientific Research (Prior- ity Programme Language and Speech Technology). For the syntactic dimension of language, vari- ous instantiations of this data-oriented processing or "DOP" approach have been worked out (e.g. Bod (1992-1995); Charniak (1996); Tugwell (1995); Sima'an et al. (1994); Sima'an (1994; 1996a); Goodman (1996); Rajman (1995ab); Kaplan (1996); Sekine and Grishman (1995)). A method for ex- tending it to the semantic domain was first intro- duced by van den Berg et al. (1994). In the present paper we discuss a computationally effective version of that method, and an implemented system that uses it. We first summarize the first fully instanti- ated DOP model as presented in Bod (1992-1993). Then we show how this method can be straightfor- wardly extended into a semantic analysis method, if corpora are created in which the trees are enriched with semantic annotations. Finally, we discuss an implementation and report on experiments with two semantically analyzed corpora (ATIS and OVIS). 2 Data-Oriented Syntactic Analysis So far, the data-oriented processing method has mainly been applied to corpora with simple syntac- tic annotations, consisting of labelled trees. Let us illustrate this with a very simple imaginary example. Suppose that a corpus consists of only two trees: S S NP VP NP VP Det N sings Det N whistles I I I I every woman a man Figure 1: Imaginary corpus of two trees We employ one operation for combining subtrees, called composition, indicated as o; this …

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