/LSDSem 2017 - Linking Models of Lexical, Sentential and Discourse-level Semantics

Past work on computational models of semantics is often fragmented across different levels of semantics, with developments in one level disconnected from the others. LSDSem aims to provide a venue for researchers from lexical, sentential and discourse-level semantics to interact, encouraging the development of models of natural language understanding that use multiple levels of semantics.
LSDSem 2017 will continue the theme of linking lexical, sentential, and discourse-level semantics, and submissions describing efforts in these areas are strongly encouraged. This includes core research on joint or ensemble models, new evaluations to measure different levels semantics, and applications that require more than one level of semantics to solve.
In addition, this year we have an additional focus on the comprehensive understanding of narrative structure in language. Recently a range of tasks have been proposed in the area of learning and applying commonsense/procedural knowledge. Such tasks include, for example, learning prototypical event sequences and event participants, modeling the plot structure of novels, and resolving anaphora in Winograd schemas. Knowledge on the level of scripts and narratives is not only useful to represent stories, recipes, and how-to instructions in a meaningful way, but can also be applied in downstream applications. Examples include, in particular, applications that require reasoning on the document level.
With respect to the area of focus, LSDSem 2017 will include two special sessions: a shared task session (see below) and a discussion session on challenges related to new datasets, evaluation techniques, and models for richer semantics.