[PDF] Top 20 A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification

... For implicit sense classification, the key is how to effectively capture the interactions between the two ...mon neural hidden layers might be insufficient to deal with the ...erful neural ... See full document

... Implicit discourse relation recognition is an extremely challenging task due to the lack of indicative ...Various neural network architectures have been proposed for this task recently, but ... See full document

... methods remain the most effective approaches. RNNs, especially the long-short term memory (LSTM) (Hochreiter and Schmidhuber, 1997) models, have been widely used to encode a para- graph for machine translation (Sutskever ... See full document

... in implicit discourse relation classification lies in extracting relevant information for the relation label from (the combination of) the discourse relational ...with ... See full document

... Recurrent neural networks, especially LSTM networks, have changed the paradigm of deriving distributed features from a sentence (Hochreiter and Schmidhuber, 1997), but they have not been much explored in the realm ... See full document

... by stacking multiple gated convolution lay- ers, and fully represents the sentence-level seman- tic ...the neural tensor network used in Guo et ... See full document

... for discourse relation classifi- cation have increasingly relied on neural network architectures (Ji et ...deep neural network archi- tectures, the demand for more reliable annotated data has ... See full document

... One fatal weakness of vanilla RNN/RNTN is the well-known gradient exploding or vanishing problem due to the multiple computation steps in the vertical direction. Therefore Tai et al. (2015) and Zhu et al. (2015) propose ... See full document

... ing word pairs as well as other rich linguistic fea- tures to automatically identify the top-level PDTB relations. Park and Cardie (2012) achieved a higher performance by optimizing the feature set. McKeown and Biran ... See full document

... utilizing implicit connectives at training time. 3) “Ensemble” has the same neural architecture with the proposed framework except that the input of a-CNN is not augmented with implicit ...two ... See full document

... tingency” relation and the sentence matches our pattern ...“Contingency” discourse relation pair and the two arguments are “they had a $5 off the price” and “i bought ... See full document

... Figure 1 (a)-(c) shows the learning curve of the implicit classifier for all input types and architec- tures. The baseline corresponds to the word pair classifier with an accuracy of 0.25. We can observe that ... See full document

... classification performance of Goal Oriented Radial Basis Architecture, Generalized Gaussian. Neural Network Architecture and Probabilistic Neural Network Architecture is [r] ... See full document

... this way, they represent words in the space of con- nectives to directly encode their discourse func- tion. The major limitation of their approach is that the dimension of the word representations must be less ... See full document

... of discourse relat ion recognition is to identify and label the relations between sentences/clauses, wh ich is funda mental to many natural language processing applications such as question answering, automatic ... See full document

... gold-truth implicit connectives, the previous state-of-art performance achieved by (Pitler et ...gold-truth implicit connectives directly to the relation’s ...Expansion relation, (Pitler et ...EntRel ... See full document

... binary classification task: the model is trained to distinguish the original following sentence from a randomly chosen sentence from the corpus, and it showed great helps in multiple NLP tasks espe- cially ... See full document

... In general, all approaches to learn from structure fall into one of three groups: linearization ap- proaches, which decompose a structure into parts that can be presented to a linear classifier as a binary feature, ... See full document

... cases, discourse relations contain an ex- plicit marker such as but or because which makes it easy to identify the ...the relation can be dis- ambiguated with f-scores higher than ... See full document

... annotated discourse parsing datasets, with 16,224 implicit ...port discourse parsing algorithms to new ...cific discourse relations must be identified, which would be difficult to achieve ... See full document