[PDF] Top 20 Attention for Implicit Discourse Relation Recognition

... underlined discourse connective connects the first dis- course argument (in italic) to the second discourse argu- ment (in bold) via a temporal ...identify discourse relations. In fact, given two ... See full document

... multi-level attention model that simulates the repeated reading process by stacking multiple attention layers with external memory; (2) R¨onnqvist (R¨onnqvist et ...with attention mechanism that ... See full document

... recognizing implicit relation has to rely solely on two textual arguments, and it must capture latent semantic and logical relationship between two arguments in ...for discourse relation ... See full document

... PDTB (Prasad et al., 2008) is the largest hand- annotated corpus of discourse relation so far. It contains 2, 312 Wall Street Journal (WSJ) articles. The sense label of discourse relations is ... See full document

... First, sections 0-2 and 21-22 of the PDTB are used as the validation and test set, respectively. Then, we randomly down-sample sections 2-20 to construct training sets for each of the classifiers, where each set has the ... See full document

... training and development data only) to balance their frequencies against single-argument samples. Two lines of motivation support the inclusion of single argument training examples, grounded in linguistics and machine ... See full document

... utilizing implicit connectives at training ...with implicit connectives. This essen- tially is an ensemble of two implicit recognition ...the implicit connectives based on the network ... See full document

... self should make self-relevant information more accessible and, as a result, should decrease latencies for recognizing words related to the self. In Study 1, people completed measures of dispositional self-focus. Persons ... See full document

... All prior work has resorted to downsampling the training data for binary classifiers to distin- guish a particular relation and use the full train- ing set for multi-class prediction. In this pa- per we compare ... See full document

... We propose that the sparsity of production rules can be reduced even further by introducing a new representation of the parse tree. Specifically, in- stead of having full production rules where a sin- gle feature records ... See full document

... 2014). Discourse parsing is also the shared task of CoNLL 2015 and 2016 (Xue et ...a discourse parser, implicit relation recognition has been the bottleneck due to lack of explicit ... See full document

... of implicit discourse relation clas- sification when no explicit discourse connective phrase was ...two discourse units by exploiting interactions between words in two units with more ... See full document

... course relation identification models on dialogue data and our proposed features, we build on the Deep Enhanced Representation (DER) model of Bai and Zhao (2018) 7 , which demonstrated its ef- ficiency by ... See full document

... contains discourse annotations over 2,312 Wall Street Jour- nal articles, and is organized in different ...each relation, we randomly ex- tracted the same number of positive and negative instances as ... See full document

... main implicit relation classifi- cation task, contain the task of predicting previ- ously removed connectives for explicit relations, and profit from shared representations between the ...both ... See full document

... Theory Discourse Treebank (RSTDT) (Carlson et ...human-annotated discourse in- ...including Implicit, Explicit, and AltLex, and with the relation types at three ...on discourse ... 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

... capture discourse relation- ships between arguments (Zhang et ...ignoring discourse information ...to discourse relations would further boost the ... 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, ... See full document

... dicted implicit connectives achieved an compara- ble performance to (Pitler et ...for implicit relation recognition and these 4 features are easy computable and fast run, which makes the ... See full document