The CL-SCisumm track provides a framework to evaluate systems summarising scientific papers. It includes datasets and metrics provided by the organisers. The track comprises three tasks: (1a) identifying the spans of text in the referred document reflecting citing ext spans i.e., citances), (1b) classifying discourse facets ofthe cited text spans, and (2) generating a short structured summary. For the 2019 edi-tion, we focused our work on the task 1a. This report presents our proposed approachfor this task. We submitted 15 runs corresponding to different configurations of theparameters involved in our approach.