%0 Conference Proceedings %T A Flexible and Easy-to-use Semantic Role Labeling Framework for Different Languages %A Do, Quynh Ngoc Thi %A Leeuwenberg, Artuur %A Heyman, Geert %A Moens, Marie-Francine %Y Zhao, Dongyan %S Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations %D 2018 %8 August %I Association for Computational Linguistics %C Santa Fe, New Mexico %F do-etal-2018-flexible %X This paper presents a flexible and open source framework for deep semantic role labeling. We aim at facilitating easy exploration of model structures for multiple languages with different characteristics. It provides flexibility in its model construction in terms of word representation, sequence representation, output modeling, and inference styles and comes with clear output visualization. The framework is available under the Apache 2.0 license. %U https://aclanthology.org/C18-2035 %P 161-165