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Transition-based Neural Constituent Parsing
Taro Watanabe
|
Eiichiro Sumita
|
Paper Details:
Month: July
Year: 2015
Location: Beijing, China
Venue:
ACL |
IJCNLP |
Citations
URL
Two Local Models for Neural Constituent Parsing
Zhiyang Teng
|
Yue Zhang
|
Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles
James Cross
|
Liang Huang
|
Sequence-to-Sequence Learning as Beam-Search Optimization
Sam Wiseman
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Alexander M. Rush
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evision PDF of 'LSTM Shift-Reduce CCG Parsing
Wenduan Xu
|
End-to-End Neural Relation Extraction with Global Optimization
Meishan Zhang
|
Yue Zhang
|
Guohong Fu
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Transition-Based Disfluency Detection using LSTMs
Shaolei Wang
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Wanxiang Che
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Yue Zhang
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Meishan Zhang
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Ting Liu
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A Neural Transition-based Model for Nested Mention Recognition
Bailin Wang
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Wei Lu
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Yu Wang
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Hongxia Jin
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Dynamic Oracles for Top-Down and In-Order Shift-Reduce Constituent Parsing
Daniel Fernández-González
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Carlos Gómez-Rodríguez
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Evaluating a Deterministic Shift-Reduce Neural Parser for Constituent Parsing
Hao Zhou
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Yue Zhang
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Shujian Huang
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Xin-Yu Dai
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Jiajun Chen
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Expected F-Measure Training for Shift-Reduce Parsing with Recurrent Neural Networks
Wenduan Xu
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Michael Auli
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Stephen Clark
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Shift-Reduce CCG Parsing using Neural Network Models
Bharat Ram Ambati
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Tejaswini Deoskar
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Mark Steedman
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Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning
Yulia Tsvetkov
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Sunayana Sitaram
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Manaal Faruqui
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Guillaume Lample
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Patrick Littell
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David Mortensen
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Alan W Black
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Lori Levin
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Chris Dyer
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Parsing Speech: a Neural Approach to Integrating Lexical and Acoustic-Prosodic Information
Trang Tran
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Shubham Toshniwal
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Mohit Bansal
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Kevin Gimpel
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Karen Livescu
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Mari Ostendorf
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Transition-Based Neural Word Segmentation
Meishan Zhang
|
Yue Zhang
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Guohong Fu
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Globally Normalized Transition-Based Neural Networks
Daniel Andor
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Chris Alberti
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David Weiss
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Aliaksei Severyn
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Alessandro Presta
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Kuzman Ganchev
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Slav Petrov
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Michael Collins
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Straight to the Tree: Constituency Parsing with Neural Syntactic Distance
Yikang Shen
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Zhouhan Lin
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Athul Paul Jacob
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Alessandro Sordoni
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Aaron Courville
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Yoshua Bengio
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An Empirical Study of Building a Strong Baseline for Constituency Parsing
Jun Suzuki
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Sho Takase
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Hidetaka Kamigaito
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Makoto Morishita
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Masaaki Nagata
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Easy-First Dependency Parsing with Hierarchical Tree LSTMs
Eliyahu Kiperwasser
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Yoav Goldberg
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Shift-Reduce Constituent Parsing with Neural Lookahead Features
Jiangming Liu
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Yue Zhang
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In-Order Transition-based Constituent Parsing
Jiangming Liu
|
Yue Zhang
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Encoder-Decoder Shift-Reduce Syntactic Parsing
Jiangming Liu
|
Yue Zhang
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Reducing Lexical Features in Parsing by Word Embeddings
Hiroya Komatsu
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Ran Tian
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Naoaki Okazaki
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Kentaro Inui
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http://github.com/tarowatanabe/trance
http://nlp.stanford.edu/software/
https://code.google.com/p/
http://nlp.cs.nyu.edu/evalb/
http://nlp.stanford.edu/software/
http://sourceforge.net/projects/zpar/
https://code.google.com/p/
Field Of Study
Task
Tagging
Machine Translation
Approach
Deep Learning
Kernel Method
Discriminative Model
Semi-supervised Learning
Language
Chinese
English
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