Neural Nets for NLP 2017 - Transition-Based Dependency Parsing

Neural Nets for NLP 2017 - Transition-Based Dependency Parsing

Graham Neubig via YouTube Direct link

Tree-structured LSTM (Tai et al. 2015)

10 of 13

10 of 13

Tree-structured LSTM (Tai et al. 2015)

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Neural Nets for NLP 2017 - Transition-Based Dependency Parsing

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

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