Greedy Transition-Based Dependency Parsing with Stack LSTMs
We introduce a greedy transition-based parser that learns to represent parser states using recurrent neural networks. Our primary innovation that enables us to do this efficiently is a new control structure for sequential neural networks—the stack long short-term memory unit (LSTM). Like the convent...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2017-03-01
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| Series: | Computational Linguistics |
| Online Access: | http://dx.doi.org/10.1162/coli_a_00285 |