This paper presents a supervised Aspect Based Sentiment Analysis (ABSA) system. Our aim is to develop a modular platform which allows to easily conduct experiments by replacing the modules or adding new features. We obtain the best result in the Opinion Target Extrac-tion (OTE) task (slot 2) using an off-the-shelf sequence labeler. The target polarity classi-fication (slot 3) is addressed by means of a multiclass SVM algorithm which includes lex-ical based features such as the polarity values obtained from domain and open polarity lex-icons. The system obtains accuracies of 0.70 and 0.73 for the restaurant and laptop domain respectively, and performs second best in the out-of-domain hotel, achieving an accuracy of 0.80. 1