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We report improved AMR parsing results by adding a new action to a transition-based AMR parser to infer abstract concepts and by incorporating richer features produced by auxiliary analyzers such as a semantic role labeler and a coreference resolver. We report final AMR parsing results that show an improvement of 7% absolute in F 1 score over the best(More)
This paper describes CAMR, the transition-based parser that we use in the SemEval-2016 Meaning Representation Parsing task. The main contribution of this paper is a description of the additional sources of information that we use as features in the parsing model to further boost its performance. We start with our existing AMR parser and experiment with(More)
Neural attention models have achieved great success in different NLP tasks. However , they have not fulfilled their promise on the AMR parsing task due to the data sparsity issue. In this paper, we describe a sequence-to-sequence model for AMR parsing and present different ways to tackle the data sparsity problem. We show that our methods achieve(More)
As one of the most important reversible protein post-translation modifications, ubiquitination has been reported to be involved in lots of biological processes and closely implicated with various diseases. To fully decipher the molecular mechanisms of ubiquitination-related biological processes, an initial but crucial step is the recognition of(More)
AIM To study the SSTR1, 2, 3, 4, 5 expression and their relationships with clinico-pathological factors, cell proliferation, Bcl-2 and p53 expression in colorectal cancer cells. METHODS Immunohistochemical staining of five SSTR subtypes, Ki-67, Bcl-2 and p53 was performed by the standard streptavidin-peroxidase (SP) technique for the paraffin sections of(More)
The CoNLL-2016 Shared Task is the second edition of the CoNLL-2015 Shared Task, now on Multilingual Shallow discourse parsing. Similar to the 2015 task, the goal of the shared task is to identify individual discourse relations that are present in natural language text. Given a natural language text, participating teams are asked to locate the discourse(More)
K(ATP) channels are metabolic sensors and targets of potassium channel openers (KCO; e.g., diazoxide and pinacidil). They comprise four sulfonylurea receptors (SUR) and four potassium channel subunits (Kir6) and are critical in regulating insulin secretion. Different SUR subtypes (SUR1, SUR2A, SUR2B) largely determine the metabolic sensitivities and the(More)