Abstract The CoNLL-2015 Shared Task is on Shallow Discourse Parsing, a task focusing on
identifying individual discourse relations that are present in a natural language text. A …

We describe our contribution to the CoNLL 2016 Shared Task on shallow discourse parsing.
1 Our system extends the two best parsers from previous year's competition by integration of …

This paper studies a novel model that simplifies the disambiguation of connectives for
explicit discourse relations. We use a neural approach that integrates contextualized word …

Argument labeling of explicit discourse relations is a challenging task. The state of the art
systems achieve slightly above 55% F-measure but require hand-crafted features. In this …

Dropped pronoun (DP) is a common problem in dialogue machine translation, in which
pronouns are frequently dropped in the source sentence and thus are missing in its …

The output of automatic translation systems is usually destined for human consumption. In
most cases, translators use machine translation (MT) as the first step in the process of …

This paper describes a novel approach for the task of end-to-end argument labeling in
shallow discourse parsing. Our method describes a decomposition of the overall labeling …

This paper describes our system for the CoNLL-2016 Shared Task on Shallow Discourse
Parsing on English. We adopt a cascaded framework consisting of nine components, among …

This paper describes the discourse parsing system developed at Dublin City University for
participation in the CoNLL 2015 shared task. We participated in two tasks: a connective and …

Statistical machine translation (SMT) plays more and more important role now. The
performance of the SMT is largely dependent on the size and quality of training data. But the …