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Word vector space specialisation models offer a portable, light-weight approach to fine-tuning arbitrary distributional vector spaces to discern between synonymy and antonymy. Their effectiveness is drawn from external linguistic constraints that specify the exact lexical relation between words. In this work, we show that a careful selection of the external constraints can steer and improve the specialisation. By simply selecting appropriate constraints, we report state-of-the-art results on adoi:10.18653/v1/w18-3018 dblp:conf/rep4nlp/Vulic18 fatcat:4estw2vheba2ziqi7vinnvefma