[PDF] Top 20 Transition based Neural Constituent Parsing
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Transition based Neural Constituent Parsing
... Constituent parsing is typically modeled by a chart-based algorithm under prob- abilistic context-free grammars or by a transition-based algorithm with rich fea- ...a neural ... See full document
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A Neural Probabilistic Structured Prediction Model for Transition Based Dependency Parsing
... With this ranking model, beam search and early-update are used. Given a training instance, the negative example is the incorrectly predicted output with largest score (Zhang and Nivre, 2011). However, we find that the ... See full document
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Efficient Structured Inference for Transition Based Parsing with Neural Networks and Error States
... (greedy parsing) to 4 gives only very modest improvements in accu- racy when trained without error states (Local–14– pre and ...arc-standard parsing with locally normalized models does not produce large ... See full document
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Stack propagation: Improved Representation Learning for Syntax
... for parsing is very simple: we use the hidden layer of a window-based POS tagging network as the representation of tokens in a greedy, transition-based neural network ...for ... See full document
10
Transition based Spinal Parsing
... and constituent structure ...of constituent triplets), the unlabeled attachment accuracy does not drop and the labeling accuracy (for the triplets) is good enough for getting a good phrase-structure ... See full document
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Distilling Knowledge for Search based Structured Prediction
... In Section 4.2, improvements from distilling the ensemble have been witnessed in both the transition-based dependency parsing and neural machine translation experiments. However, ques- tions ... See full document
10
Evaluating a Deterministic Shift Reduce Neural Parser for Constituent Parsing
... deterministic transition-based constituent ...with neural dependency parsing (Table ...a transition-based constituent parser is much larger than in a dependency ... See full document
5
Joint POS Tagging and Transition based Constituent Parsing in Chinese with Non local Features
... state-of-the-art transition-based constituent ...of parsing models, we enlarge the fea- ture set with non-local features and semi- supervised word cluster ...improve parsing performance ... See full document
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Transition Based Dependency Parsing with Heuristic Backtracking
... 2014. Neural machine translation by jointly learning to align and ...A transition- based system for joint part-of-speech tagging and la- beled non-projective dependency ... See full document
6
Bidirectional Transition-Based Dependency Parsing
... memory based learning (Attardi 2006), multi- class averaged perceptron (Attardi et ...learning, neural networks have recently been used to train dependency parsers (Stenetorp 2013; Chen and Manning 2014; ... See full document
8
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
Constituent Parsing with Incremental Sigmoid Belief Networks
... for constituent parsing based on dynamic Sigmoid Belief Networks with vectors of latent ...the neural network parser of (Henderson, 2003) can be considered as a simple feed-forward ... See full document
8
Fast and Accurate Shift Reduce Constituent Parsing
... to transition-based phrase-structure (constituent) parsing also (Zhang and Clark, 2009), maintaining all the afore- mentioned ...for transition-based depen- dency ...of ... See full document
10
Chinese NER with Height-Limited Constituent Parsing
... For the overall entities, the unified model is observed to outperform previous character-based methods by 2.79 points in F1 (from 73.88% to 76.67%), and it also outperforms pre- vious word-based method with ... See full document
8
Multi Task Semantic Dependency Parsing with Policy Gradient for Learning Easy First Strategies
... train transition-based parsers with reinforcement learn- ing: Zhang and Chan (2009) applied SARSA (Baird III, 1999) to an Arc-Standard model, us- ing SARSA updates to fine-tune a model that was pre-trained ... See full document
11
Transition Based Chinese AMR Parsing
... the transition-based constituent parser in (Wang and Xue, 2014) to first parse the Chinese sentences into constituent trees, which are then transformed into dependency trees using the ... See full document
6
Transition based Dependency Parsing Using Two Heterogeneous Gated Recursive Neural Networks
... Figure 1 gives a rough sketch for the standard RNN, Tree-GRNN and DAG-GRNN. Tree-GRNN is applied to the partial-constructed trees in stack, which have already been constructed according to the previous transition ... See full document
11
TRANX: A Transition based Neural Abstract Syntax Parser for Semantic Parsing and Code Generation
... a transition system that de- composes the generation procedure of an AST into a sequence of tree-constructing ...the transition system using our running ex- ... See full document
6
Structured Training for Neural Network Transition Based Parsing
... compare using the estimates P(y) from the neural network directly for beam search to using the acti- vations from all layers as features in the structured perceptron. Using the probability estimates di- rectly is ... See full document
11
Transition based dependency parsing as latent variable constituent parsing
... of transition-based de- pendency parsing and the theory of constituent ...of constituent parsing that is based on latent-variable probabilistic context-free grammars, ... See full document
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