A participant system is given a piece of newswire text as input and returns discourse relations in the form of a discourse connective (explicit or implicit) taking two arguments (which can be clauses, sentences, or multi-sentence segments). Specifically, the participant system needs to i) locate both explicit (e.g., "because", "however", "and".) discourse connectives in the text, ii) identify the spans of text that serve as the two arguments for each discourse connective, and iii) predict the sense of the discourse connectives (e.g., "Cause", "Condition", "Contrast"). Understanding such discourse relations is clearly an important part of natural language understanding that benefits a wide range of natural language applications. More detail and examples
The best performing system is from Jianxiang Wang and Man Lan from East China Normal University, Shanghai. The F1 scores are 29.72 and 24.00 on the WSJ test set and the blind test set respectively. Supplemental evaluation results and overview papers can be found here. The code for this system is provided for forking here.
The Shared Task has now concluded for this year. Please stay tuned for the next round in 2016.