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We describe our experiments using the DeSR parser in the multilingual and do- main adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incre- mental deterministic Shift/Reduce parsing …...

Deterministic parsing has emerged as an ef- fective alternative for complex parsing algo- rithms which search the entire search space to get the best probable parse tree. In this pa- …...

This paper presents a first-order logic learn- ing approach to determine rhetorical relations between discourse segments. Beyond lin- guistic cues and lexical information, our ap- proach exploits compositional semantics and …...

We apply the graph-structured stack (GSS) to shift-reduce parsing in a Combinatory Cate- gorial Grammar (CCG) parser. This allows the shift-reduce parser to explore all possible parses in polynomial time …...

We introduce a shift-reduce parsing algorithm for phrase-based string-to- dependency translation. As the algorithm generates dependency trees for partial translations left-to-right in decoding, it allows for efficient integration of both …...

Recent work on Chinese analysis has led to large-scale annotations of the internal structures of words, enabling character- level analysis of Chinese syntactic struc- tures. In this paper, we investigate …...

We propose an algorithm for coreference resolution based on analogy with shift-reduce pars- ing. By reconceptualising the task in this way, we unite ranking- and cluster-based approaches to coreference resolution, …...

AbstractWe present supertagging-based models for Tree Adjoining Grammar parsing that use neural network architectures and dense vector representation of supertags (elementary trees) to achieve state-of-the-art performance in unlabeled and labeled …...