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Intro
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Classroom Contents
Neural Nets for NLP - Transition-based Parsing
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- 1 Intro
- 2 Two Types of Linguistic Structure
- 3 Why Dependencies?
- 4 Arc Standard Shift-Reduce Parsing (Yamada & Matsumoto 2003, Nivre 2003)
- 5 Shift Reduce Example
- 6 Classification for Shift-reduce
- 7 Making Classification Decisions
- 8 Non-linear Function: Cube Function
- 9 Why Tree Structure?
- 10 Recursive Neural Networks (Socher et al. 2011)
- 11 Encoding Parsing Configurations w/ RNNS
- 12 Alternative Transition Methods
- 13 Shift-reduce Parsing for Phrase Structure (Sagae and Lavie 2006. Watanabe 2015) . Shift, reduce X (binary), unary-X (unary) where X is a label
- 14 A Simple Approximation: Linearized Trees (Vinyals et al. 2015)
