The fine-grained task of automatically detecting all sentiment expressions within a given document and the aspects to which they refer is known as aspect-based sentiment analysis. In this paper we present the first full aspect-based sentiment analysis pipeline for Dutch
and apply it to customer reviews. To this purpose, we collected reviews from two different domains, i.e. restaurant and smartphone reviews. Both corpora have been manually annotated using newly developed guidelines that comply to standard practices in the field. For our experimental pipeline we perceive aspect-based sentiment analysis as a task consisting of three main subtasks which have to be tackled incrementally: aspect term extraction, aspect category classification and polarity classification. First experiments on our Dutch restaurant corpus reveal that this is indeed a feasible approach that yields promising results.