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.- Anthology ID:
- Q16-1032
- Volume:
- Transactions of the Association for Computational Linguistics, Volume 4
- Month:
- Year:
- 2016
- Address:
- Cambridge, MA
- Editors:
- Lillian Lee, Mark Johnson, Kristina Toutanova
- Venue:
- TACL
- SIG:
- Publisher:
- MIT Press
- Note:
- Pages:
- 445–461
- Language:
- URL:
- https://aclanthology.org/Q16-1032
- DOI:
- 10.1162/tacl_a_00110
- Cite (ACL):
- Eliyahu Kiperwasser and Yoav Goldberg. 2016. Easy-First Dependency Parsing with Hierarchical Tree LSTMs. Transactions of the Association for Computational Linguistics, 4:445–461.
- Cite (Informal):
- Easy-First Dependency Parsing with Hierarchical Tree LSTMs (Kiperwasser & Goldberg, TACL 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/Q16-1032.pdf