Joint RNN-Based Greedy Parsing and Word Composition

Understand

This paper introduces a greedy parser based on neural networks, which leverages a new compositional sub-tree representation.

• The greedy parser and the compositional procedure are jointly trained, and tightly depends on each-other.
• The composition procedure outputs a vector representation which summarizes syntactically (parsing tags) and semantically (words) sub-trees.
• Composition and tagging is achieved over continuous (word or tag) representations, and recurrent neural networks.