This paper describes a heuristic for morphemeand morphology-learning based on string edit distance. Experiments with a 7,000 word corpus of Swahili, a language with a rich morphology, support the effectiveness of this approach.
It is argued in this paper that an optimal solution to disambiguation is a combination of linguistically motivated rules and resolution based on probability or heuristic rules. By disambiguation is here meant ambiguity resolution on all levels of language analysis, including morphology and semantics. The discussion is based on Swahili, for which a comprehensive analysis system has been develope...
