Sense-Linking in a Machine Readable Dictionary

Sense-Linking in a Machine Readable Dictionary Robert Krovetz Department of Computer Science University of Massachusetts, Amherst, MA 01003 Abstract (LDOCE), is a dictionary for learners of English as Dictionaries contain a rich set of relation- ships between their senses, but often these relationships are only implicit. We report on our experiments to automatically iden- tify links between the senses in a machine- readable dictionary. In particular, we au- tomatically identify instances of zero-affix morphology, and use that information to find specific linkages between senses. This work has provided insight into the perfor- mance of a stochastic tagger. 1 Introduction Machine-readable dictionaries contain a rich set of relationships between their senses, and indicate them in a variety of ways. Sometimes the relation- ship is provided explicitly, such as with a synonym or antonym reference. More commonly the relationship is only implicit, and needs to be uncovered through outside mechanisms. This paper describes our ef- forts at identifying these links. The purpose of the research is to obtain a bet- ter understanding of the relationships between word meanings, and to provide data for our work on word- sense disambiguation and information retrieval. Our hypothesis is that retrieving documents on the basis of word senses (instead of words) will result in bet- ter performance. Our approach is to treat the in- formation associated with dictionary senses (part of speech, subcategorization, subject area codes, etc.) as multiple sources of evidence (cf. Krovetz [3]). This process is fundamentally a divisive one, and each of the sources of evidence has exceptions (i.e., instances in which senses are related in spite of be- ing separated by part of speech, subcategorization, or morphology). Identifying related senses will help us to test the hypothesis that unrelated meanings will be more effective at separating relevant from nonrelevant documents than meanings which are re- lated. We will first discuss some of the explicit indica- tions of sense relationships as found in usage notes and deictic references. We will then describe our efforts at uncovering the implicit relationships via stochastic tagging and word collocation. 2 Explicit Sense Links The dictionary we are using in our research, the Longman Dictionary of Contemporary English a second language. As such, it provides a great deal of information about word meanings in the form of example sentences, usage notes, and gram- mar codes. The Longman dictionary is also unique among learner's dictionaries in that its definitions are generally written using a controlled vocabulary of approximately 2200 words. When exceptions oc- cur they are indicated by means of a different font. For example, consider the definition of the word gravity: • gravity n lb. worrying importance: He doesn't understand the gravity of his illness - see GRAVE 2 • grave adj 2. important and needing attention and (often) worrying: This is grave news -- The sick man's condition is grave These definitions serve to illustrate how words can be synonymous 1 even though they have different parts of speech. They also indicate how the Long- man dictionary …

Content truncated to 500 words