Influence of accurate compound noun splitting on bilingual vocabulary extraction

The influence of compound noun splitting on a German-Polish bilingual vocabulary extraction task is investigated. To accomplish this, several unsupervised methods for increasingly accurate compound noun splitting are introduced. Bilingual evidence from a parallel German-Polish corpus and co-occurrence counts from the web are used to disambiguate compound noun analyses directly. These collected splits serve as training data for a probabilistic model that abstracts away from the errors made by the direct methods and reaches an f-measure of 95.10%. Furthermore, these methods are evaluated in terms of word alignment quality and extraction accuracy where linguistically accurate methods are found to outperform the corpus-based methods proposed in the literature. A comparison of alignment quality achieved with the best splitting method and the baseline implies that the effort to build supervised splitting methods might result in minimal or no performance gains.