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Improved Transition-Based Parsing and Tagging with Neural Networks
Chris Alberti
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David Weiss
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Greg Coppola
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Slav Petrov
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Paper Details:
Month: September
Year: 2015
Location: Lisbon, Portugal
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Bi-directional Attention with Agreement for Dependency Parsing
Hao Cheng
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Hao Fang
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Xiaodong He
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Jianfeng Gao
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Li Deng
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A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
Kazuma Hashimoto
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Caiming Xiong
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Yoshimasa Tsuruoka
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Richard Socher
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Identifying Well-formed Natural Language Questions
Manaal Faruqui
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Dipanjan Das
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Improved Dependency Parsing using Implicit Word Connections Learned from Unlabeled Data
Wenhui Wang
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Baobao Chang
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Mairgup Mansur
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Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing
Minh Lê
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Antske Fokkens
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Towards Accurate and Efficient Chinese Part-of-Speech Tagging
Weiwei Sun
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Xiaojun Wan
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The parse is darc and full of errors: Universal dependency parsing with transition-based and graph-based algorithms
Kuan Yu
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Pavel Sofroniev
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Erik Schill
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Erhard Hinrichs
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A Novel Neural Network Model for Joint POS Tagging and Graph-based Dependency Parsing
Dat Quoc Nguyen
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Mark Dras
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Mark Johnson
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An Improved Neural Network Model for Joint POS Tagging and Dependency Parsing
Dat Quoc Nguyen
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Karin Verspoor
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IBM Research at the CoNLL 2018 Shared Task on Multilingual Parsing
Hui Wan
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Tahira Naseem
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Young-Suk Lee
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Vittorio Castelli
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Miguel Ballesteros
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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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Making Dependency Labeling Simple, Fast and Accurate
Tianxiao Shen
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Tao Lei
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Regina Barzilay
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Right-truncatable Neural Word Embeddings
Jun Suzuki
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Masaaki Nagata
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Non-Projective Dependency Parsing with Non-Local Transitions
Daniel Fernández-González
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Carlos Gómez-Rodríguez
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Generalized Transition-based Dependency Parsing via Control Parameters
Bernd Bohnet
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Ryan McDonald
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Emily Pitler
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Ji Ma
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Stack-propagation: Improved Representation Learning for Syntax
Yuan Zhang
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David Weiss
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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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Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings
Bernd Bohnet
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Ryan McDonald
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Gonçalo Simões
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Daniel Andor
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Emily Pitler
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Joshua Maynez
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http://ufal.mff.cuni.cz/conll2009-st/results/results.php
Field Of Study
Linguistic Trends
Embeddings
Morphology
Task
Tagging
Approach
Semi-supervised Learning
Language
Multilingual
Chinese
English
Japanese
Spanish
Dataset
News
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