Neural Nets for NLP - Transition-based Parsing

Neural Nets for NLP - Transition-based Parsing

Graham Neubig via YouTube Direct link

Non-linear Function: Cube Function

8 of 14

8 of 14

Non-linear Function: Cube Function

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Neural Nets for NLP - Transition-based Parsing

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

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