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Greed is Good if Randomized: New Inference for Dependency Parsing
Yuan Zhang
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Tao Lei
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Regina Barzilay
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Tommi Jaakkola
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Paper Details:
Month: October
Year: 2014
Location: Doha, Qatar
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Mise en Place: Unsupervised Interpretation of Instructional Recipes
Chloé Kiddon
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Ganesa Thandavam Ponnuraj
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Luke Zettlemoyer
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Yejin Choi
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Effective Greedy Inference for Graph-based Non-Projective Dependency Parsing
Ilan Tchernowitz
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Liron Yedidsion
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Roi Reichart
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Global Neural CCG Parsing with Optimality Guarantees
Kenton Lee
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Mike Lewis
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Luke Zettlemoyer
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Incremental Graph-based Neural Dependency Parsing
Xiaoqing Zheng
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PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies
Manuela Sanguinetti
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Cristina Bosco
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Alberto Lavelli
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Alessandro Mazzei
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Oronzo Antonelli
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Fabio Tamburini
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High-Order Low-Rank Tensors for Semantic Role Labeling
Tao Lei
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Yuan Zhang
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Lluís Màrquez
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Alessandro Moschitti
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Regina Barzilay
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Template Kernels for Dependency Parsing
Hillel Taub-Tabib
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Yoav Goldberg
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Amir Globerson
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Joint Case Argument Identification for Japanese Predicate Argument Structure Analysis
Hiroki Ouchi
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Hiroyuki Shindo
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Kevin Duh
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Yuji Matsumoto
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Neural Network-Based Model for Japanese Predicate Argument Structure Analysis
Tomohide Shibata
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Daisuke Kawahara
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Sadao Kurohashi
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Deep Multitask Learning for Semantic Dependency Parsing
Hao Peng
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Sam Thomson
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Noah A. Smith
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Stack-Pointer Networks for Dependency Parsing
Xuezhe Ma
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Zecong Hu
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Jingzhou Liu
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Nanyun Peng
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Graham Neubig
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Eduard Hovy
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Annotating Italian Social Media Texts in Universal Dependencies
Manuela Sanguinetti
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Cristina Bosco
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Alessandro Mazzei
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Alberto Lavelli
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Fabio Tamburini
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https://github.com/
Field Of Study
Task
Tagging
Machine Translation
Approach
Structured Prediction
Language
Chinese
English
Japanese
Spanish
Arabic
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