Easy-First Dependency Parsing with Hierarchical Tree LSTMs

Eliyahu Kiperwasser, Yoav Goldberg

Abstract


We suggest a compositional vector representation of parse trees that relies on a recursive combination of recurrent-neural network encoders. To demonstrate its effectiveness, we use the representation as the backbone of a greedy, bottom-up dependency parser, achieving very strong accuracies for English and Chinese, without relying on external word embeddings. The parser’s  implementation is available for download at the first author’s webpage.


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