Paper: Learning Morphological Disambiguation Rules For Turkish

ACL ID N06-1042
Title Learning Morphological Disambiguation Rules For Turkish
Venue Human Language Technologies
Session Main Conference
Year 2006
Authors

In this paper, we present a rule based model for morphological disambiguation of Turkish. The rules are generated by a novel decision list learning algorithm us- ing supervised training. Morphological ambiguity (e.g. lives = live+s or life+s) is a challenging problem for agglutinative languages like Turkish where close to half of the words in running text are morpho- logically ambiguous. Furthermore, it is possible for a word to take an unlimited number of suf xes, therefore the number of possible morphological tags is unlim- ited. We attempted to cope with these problems by training a separate model for each of the 126 morphological features recognized by the morphological analyzer. The resulting decision lists independently vote on each of the potential parses of a word and the nal parse...