LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test
UKP participated in the Story Cloze Test challenge at the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics (LSDSem 2017). The goal of this competition was to provide a common ground for the evaluation of systems on language understanding. Given four sentences of a story on everyday life events, a system had to identify the correct ending from a set of two predefined ending sentences.
Our system is based on a deep learning architecture combined with a rich set of manually-crafted linguistic features. The system outperformed all known baselines for the task, achieving an accuracy of 71.7 %. The system was placed fourth among 8 systems.
Further information on the task and the original dataset can be found on the competition website.
You can find the system description here:
The source code and generated training data can be downloaded from here: