[PDF] Top 20 Syntactic Dependency Representations in Neural Relation Classification
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Syntactic Dependency Representations in Neural Relation Classification
... parser representations, we create a sdp for each training example using the different parse models and exploit them as input to the relation classi- fication ...the dependency rep- ... See full document
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Complex Lexico syntactic Reformulation of Sentences Using Typed Dependency Representations
... discourse relation of causa- tion. We find typed dependency structures to be the most suited for this task and report that hand- crafted transformation rules generalise well to sen- tences in an unseen test ... See full document
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Comparing Word Representations for Implicit Discourse Relation Classification
... of syntactic parsers and lexical databases of var- ious kinds, which are available but for a few lan- guages, and they often involve heavy feature en- gineering (Pitler et ... See full document
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Improving Sequence to Sequence Neural Machine Translation by Utilizing Syntactic Dependency Information
... using dependency in- formation of words has been reported in some previous NLP tasks, for example, in dependency- based word embeddings, relation classification and sentence ... See full document
9
Neural language models as psycholinguistic subjects: Representations of syntactic state
... morphosyntactic dependency: for example, that The key to the ...This dependency turns out to be learnable from a language mod- eling objective (Gulordava et ... See full document
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Task oriented Evaluation of Syntactic Parsers and Their Representations
... is syntactic features. For dependency-based parse representations, a de- pendency path is encoded as a flat tree as depicted in Figure 6 (prefix “r” denotes reverse ... See full document
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Structural Embedding of Syntactic Trees for Machine Comprehension
... stituency tree and dependency tree into considera- tion. Such techniques have been proven to be use- ful in many natural language understanding tasks in the past and illustrated noticeable improvements such as the ... See full document
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A Position Encoding Convolutional Neural Network Based on Dependency Tree for Relation Classification
... Most of these baselines concatenate external lex- ical features to features extracted by neural network and directly pass the combined vector to classifier. SDP-LSTM represents lexical features as embed- dings and ... See full document
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Leveraging Dependency Forest for Neural Medical Relation Extraction
... Medical relation extraction discovers relations between entity mentions in text, such as re- search ...task, dependency syn- tax has been recognized as a crucial source of ...graph neural network is ... See full document
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Multiplicative Representations for Unsupervised Semantic Role Induction
... word representations (Mikolov et ...tic dependency relations between ...of syntactic dependency rela- tions in SRL, we explicitly model dependencies as multiplicative factors in neural ... See full document
6
Real valued Syntactic Word Vectors (RSV) for Greedy Neural Dependency Parsing
... transition-based dependency parsing is ap- pealing thanks to its efficiency, deriving a parse tree for a sentence in linear time using a discrimi- native ...greedy dependency parser, neu- ral network models ... See full document
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Inverted indexing for cross lingual NLP
... word representations for cross-lingual parsing ...monolingual dependency parsing, investigate continuous word representation for dependency parsing in a mono- lingual cross-domain setup and compare ... See full document
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Bidirectional Recurrent Convolutional Neural Network for Relation Classification
... traditional relation classification approaches focusing on designing effective fea- tures (Rink and Harabagiu, 2010) or kernels (Ze- lenko et ...on neural networks (NN), employing continuous ... See full document
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A Dependency Based Neural Network for Relation Classification
... a dependency tree kernel and attached more information including Part-of-Speech tag, chunking tag of each node in the ...a dependency graph concentrates most of the information for identifying the ... See full document
6
Dependency Link Embeddings: Continuous Representations of Syntactic Substructures
... In related work, Bansal et al. (2014) also use dependency context to tailor word embeddings to dependency parsing. However, their embedding features are still based on the sparse set of n-ary, word-based ... See full document
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An Iterative Approach for Joint Dependency Parsing and Semantic Role Labeling
... for syntactic dependency relation labeling and semantic role ...For syntactic dependency parsing, we use an approach with very high time and space complexity, so it is not added to the ... See full document
6
A Re ranking Model for Dependency Parser with Recursive Convolutional Neural Network
... dense representations in a dependency ...convolutional neural net- work (RCNN) architecture to capture the syntac- tic and compositional-semantic representations of phrases and ...the ... See full document
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Dependency Recurrent Neural Language Models for Sentence Completion
... Most neural language models consider the to- kens in a sentence in the order they appear, and the hidden state representation of the network is typically reset at the beginning of each sen- ...the syntactic ... See full document
7
Connecting Language and Knowledge with Heterogeneous Representations for Neural Relation Extraction
... state-of-the-art neural models and Weston over the entire range of ...the representations and biased toward ...erogeneous representations bring mutual benefits which are out of reach of previous ... See full document
6
Sequence to Dependency Neural Machine Translation
... To address these issues, we propose and empir- ically evaluate a novel Sequence-to-Dependency Neural Machine Translation (SD-NMT) model in our paper. An SD-NMT model encodes source in- puts with ... See full document
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