Parsing accuracy using efficient greedy transition systems has improved dramatically in recent years thanks to neural networks. Despite striking results in dependency parsing, however, neural models have not surpassed stateof-the-art approaches in constituency parsing. To remedy this, we introduce a new shiftreduce system whose stack contains merely sentence spans, represented by a bare minimum...

Previous researches on Text-level discourse parsing mainly made use of constituency structure to parse the whole document into one discourse tree. In this paper, we present the limitations of constituency based discourse parsing and first propose to use dependency structure to directly represent the relations between elementary discourse units (EDUs). The state-of-the-art dependency parsing tec...

Precis: This paper examines the electoral impact of the counting and transfer of lower preference votes on Dail elections since 1922. The relationship between transfers and constituency size is assessed, and it is shown that a constituency size of at least five members is needed before transfers have an even chance of affecting the final result. Only Fine Gael has benefited significantly in net...

In this paper I articulate a notion of constituency orthogonal both to classical and connectionist approaches. I shall consider three “structure-in-time” connectionist networks (Simple Recurrent Networks, Long Short-Term Memory Models, and Non-classical Connectionist Parsers). I shall argue that explaining compositionality by means of any of these models drives us to an information-processing b...