Deriving de/het gender classification for Dutch nouns for rule-based MT generation tasks
Bogdan Babych, Jonathan Geiger, Mireia Ginestí Rosell, Kurt Eberle · 2014
Linguistic resources available in the public domain, such as lemmatisers, part-ofspeech taggers and parsers can be used for the development of MT systems: as separate processing modules or as annotation tools for the training corpus.For SMT this annotation is used for training factored models, and for the rule-based systems linguistically annotated corpus is the basis for creating analysis, generation and transfer dictionaries from corpora.However, the annotation in many cases is insufficient for rule-based MT, especially for the generation tasks.In this paper we analyze a specific case when the part-ofspeech tagger does not provide information about de/het gender of Dutch nouns that is needed for our rule-based MT systems translating into Dutch.We show that this information can be derived from large annotated monolingual corpora using a set of context-checking rules on the basis of co-occurrence of nouns and determiners in certain morphosyntactic configurations.As not all contexts are sufficient for disambiguation, we evaluate the coverage and the accuracy of our method for different frequency thresholds © 2014 European Association for Computational Linguistics.in the news corpora.Further we discuss possible generalization of our method, and using it to automatically derive other types of linguistic information needed for rule-based MT: syntactic subcategorization frames, feature agreement rules and contextually appropriate collocates.