Learning Dependencies between Case Frame Slots

Learning Dependencies between Case Frame Slots Hang Li and Naoki Abe Theory NEC Laboratory, RWCP* c/o ('.&C. Research Labora.tories, NEC. 4-1-1 Miyazaki Miyama.e-l~u, Kawasaki, 2116 Japan {lih ang,abe} (~.sbl.cl.nec.co.jp Abstract We address the problem of automati- cally acquiring case frame patterns (se- lectional patterns) from large corpus data. In particular, we l)ropose a method of learning dependencies between case frame slots. We view the problem of learning case frame patterns as that of learning a multi-dimensional discrete joint distribution, where random vari- ables represent case slots. We then for- mMize the dependencies between case slots as the probabilislic dependencies between these random variables. Since the number of parameters in a multi- dimensional joint distribution is expo- nential in general, it is infeasible to ac- curately estimate them in practice. To overcome this difficulty, we settle with approximating the target joint distribu- tion by the product of low order com- ponent distributions, based on corpus data. In particular we propose to employ an efficient learning algorithm based on the MDL principle to realize this task. Our experimental results indicate that for certain classes of verbs, the accuracy achieved in a disambiguation experiment is improved by using the acquired knowl- edge of dependencies. 1 Introduction We address the problem of automatically acquir- ing case frame patterns (selectional patterns) from large corpus data. The acquisition of case frame patterns normally involves the following three subproblems: 1) Extracting case fl'ames from cor- pus data, 2) Generalizing case frame slots wMfin these case frames, 3) Learning dependencies that exist between these generalized case frame slots. In this paper, we propose a method of learn- ing dependencies between case frame slots. By *Real World Computing Partnership 'dependency' is meant the relation that exists be- tween case frame slots which constrains the pos- sible values assumed by each of those slots. As illustrative examples, consider tile following sen- tences. The girl will fly a jet. This aMine company flies many jets. The gM will fly Japan AMines. *The airline conlpany will fly ,Japan Airlines. (1) We see that an 'airline company' can be the sub- ject of verb 'fly' (the value of case slot 'argl'), when the direct object (the value of ease slot 'arg2') is an 'airplane' but not when it is an 'air- line company '1. These, examples indicate that the possible values of case slots depend in general on those of the other case slots: that is, there exist 'dependencies' between different case slots. The knowledge of such dependencies is useflfl in var- ious tasks in natural language processing, espe- cially in analysis of sentences involving multiple prepositional phrases, such as The girl will fly a jet fl'om Tokyo to Beijing. (2) Note in the above example that the case slot of 'from' and that of 'to' should be considered depen- dent and the attachment sit(." of one of the prepo- sitional phrases (case slots) can be determined by that of the other with high accuracy and confi- dence. There has been no method …

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