LSDSem-2017

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:

LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test

The source code and generated training data can be downloaded from here:

https://github.com/UKPLab/lsdsem2017-story-cloze