Morphological Disambiguation by Voting Constraints

Morphological Disambiguation by Voting Constraints Kemal Oflazer and GSkhan Tfir Department of Computer Engineering and Information Science Bilkent University, Bilkent, TR-06533, Turkey {ko, tur}©cs, bilkent, edu. tr Abstract We present a constraint-based morpholog- ical disambiguation system in which indi- vidual constraints vote on matching mor- phological parses, and disambiguation of all the tokens in a sentence is performed at the end by selecting parses that receive the highest votes. This constraint applica- tion paradigm makes the outcome of the disambiguation independent of the rule se- quence, and hence relieves the rule devel- oper from worrying about potentially con- flicting rule sequencing. Our results for disambiguating Turkish indicate that using about 500 constraint rules and some addi- tional simple statistics, we can attain a re- call of 95-96~ and a precision of 94-95~ with about 1.01 parses per token. Our sys- tem is implemented in Prolog and we are currently investigating an efficient imple- mentation based on finite state transduc- ers. 1 Introduction Automatic morphological disambiguation is an im- portant component in higher level analysis of natural language text corpora. There has been a large num- ber of studies in tagging and morphological disam- biguation using various techniques such as statisti- cal techniques, e.g., (Church, 1988; Cutting et al., 1992; DeRose, 1988), constraint-based techniques (Karlsson et al., 1995; Voutilainen, 1995b; Vouti- lainen, Heikkil/i, and Anttila, 1992; Voutilainen and Tapanainen, 1993; Oflazer and KuruSz, 1994; Oflazer and Till 1996) and transformation-based techniques (Brilt, 1992; Brill, 1994; Brill, 1995). This paper presents a novel approach to constraint based morphological disambiguation which relieves the rule developer from worrying about conflicting rule ordering requirements. The approach depends on assigning votes to constraints according to their complexity and specificity, and then letting con- straints cast votes on matching parses of a given lexical item. This approach does not reflect the out- come of matching constraints to the set of morpho- logical parses immediately. Only after all applicable rules are applied to a sentence, all tokens are dis- ambiguated in parallel. Thus, the outcome of the rule applications is independent of the order of rule applications. Rule ordering issue has been discussed by Voutilainen(1994), but he has recently indicated 1 that insensitivity to rule ordering is not a property of their system (although Voutilainen(1995a) states that it is a very desirable property) but rather is achieved by extensively testing and tuning the rules. In the following sections, we present an overview of the morphological disambiguation problem, high- lighted with examples from Turkish. We then present our approach and results. We finally con- clude with a very brief outline of our investigation into efficient implementations of our approach. 2 Morphological Disambiguation In all languages, words are usually ambiguous in their parts-of-speech or other morphological fea- tures, and may represent lexical items of different syntactic categories, or morphological structures de- pending on the syntactic and semantic context. In languages like English, there are a very small number of possible word forms that can be generated from a given root …

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