Efficient Morphological Parsing with a Weighted Finite State Transducer

This article describes a highly optimized algorithm and implementation of a deterministic weighted finite state transducer for morphological analysis. We show how various functionalities can be integrated into one machine, without sacrificing performance or flexibility, and and still maintaining applicability to various languages. The annotation schema used in this implementation maximizes interoperability and compatibility by using a direct mapping of tags from the GOLD ontology of linguistic concepts and features, providing possible extended processing scenarios.