[PDF] Top 20 A Neural Probabilistic Structured Prediction Model for Transition Based Dependency Parsing
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A Neural Probabilistic Structured Prediction Model for Transition Based Dependency Parsing
... a structured neural transition-based parser by adopting beam search and early ...Their model is close in spirit to ours in performing structured predic- tion using a ... See full document
10
Incremental Graph based Neural Dependency Parsing
... volutional neural network and constructs an initial parse graph by head-modifier predictions with a maximum directed spanning tree algorithm based on the first-order features ...arc prediction and a ... See full document
11
Transition based dependency parsing as latent variable constituent parsing
... mal model of deterministic parsing in Section 3, in terms of oracle ...constituent parsing, but Section 4 shows that they allow a clean formalization of arc-standard and arc-eager ... See full document
11
Dependency Language Models for Transition based Dependency Parsing
... features based on frequencies with the ba- sic first-/second-order ...features based on the statistics learned from unlabeled data to a weak first-order parser and they achieved ...in neural net- ... See full document
7
An Empirical Investigation of Structured Output Modeling for Graph based Neural Dependency Parsing
... Daniel Zeman, Martin Popel, Milan Straka, Jan Ha- jic, Joakim Nivre, Filip Ginter, Juhani Luotolahti, Sampo Pyysalo, Slav Petrov, Martin Potthast, Fran- cis Tyers, Elena Badmaeva, Memduh Gokirmak, Anna Nedoluzhko, Silvie ... See full document
7
Transition Based Dependency Parsing with Heuristic Backtracking
... Heuristic backtracking with cutoff outperformed greedy decoding, and reduced transitions by an addi- tional 50%. However, it increased accuracy slightly less than full heuristic backtracking. We believe this difference ... See full document
6
Neural Syntactic Generative Models with Exact Marginalization
... our model obtains state of the art performance in transition-based gener- ative dependency ...generative model has a large impact on both the informedness of the syntactic structure and ... See full document
11
A Structured Language Model Based on Context Sensitive Probabilistic Left Corner Parsing
... The SHIFT submodel implements (4 0 ). Finding a good parameterization entails fixing the features that should explicitly appear in the context and in which order, so that all information-bearing ele- ments are ... See full document
8
Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks
... Recently, neural network based depen- dency parsing has attracted much interest, which can effectively alleviate the prob- lems of data sparsity and feature engineer- ing by using the dense ... See full document
11
A Survey of Natural Language Query Builder Interface for Structured Databases using Dependency Parsing
... in transition-based models is its inability of dealing with non-projective ...pseudo-projective parsing, a preprocess step turns every non-projective arcs into projective ...the parsing ... See full document
6
Efficient Structured Inference for Transition Based Parsing with Neural Networks and Error States
... approximate structured inference for transition-based parsing that uses locally-trained neural networks that, unlike pre- vious local classification approaches, produce scores suitable ... See full document
14
Structured Training for Neural Network Transition Based Parsing
... parsers. Neural networks are known to perform very well in the presence of large amounts of training ...by parsing an unlabeled corpus and selecting only the sentences on which two different parsers ... See full document
11
Association Metrics in Neural Transition Based Dependency Parsing
... A qualitative analysis revealed that association scores in parts provide useful disambiguation cues to the parser. Follow-up experiments in other languages with relatively free word order and moderately complex ... See full document
9
A Transition based System for Universal Dependency Parsing
... for parsing between the situation of current and that of ten years ago is that recently we have seen a rising of neu- ral network based methods in the field of Natu- ral Language Processing and ... See full document
7
Transition Based Parsing for Deep Dependency Structures
... the structured perceptron algorithm (Collins 2002) for transition classification and use a beam decoder for global ...namely, transition combination and tree approximation, to improve parsing ... See full document
37
Distilling Knowledge for Search based Structured Prediction
... into structured prediction and solved as a search ...search-based structured prediction tasks – transition-based dependency pars- ing and neural machine ... See full document
10
Transition based dependency parsing as latent variable constituent parsing
... mal model of deterministic parsing in Section 3, in terms of oracle ...constituent parsing, but Section 4 shows that they allow a clean formalization of arc-standard and arc-eager ... See full document
11
Transition based Neural Constituent Parsing
... recursive neural networks for parsing, first pioneered by Costa et ...which parsing is treated as a ranking problem of finding phrasal ...under dependency parsing. Our model is ... See full document
11
Probabilistic Graph based Dependency Parsing with Convolutional Neural Network
... the parsing algorithm for inference or searching the most likely parse tree, the other is the parameter estimation approach for the machine learning ...previous neural methods (Socher et ...structure ... See full document
11
Punctuation Prediction with Transition based Parsing
... Standard automatic speech recognizers output un- structured streams of words. They neither perform a proper segmentation of the output into sentences, nor predict punctuation symbols. The unavailable punctuations ... See full document
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