@inproceedings{ballesteros-carreras-2017-arc,
title = "Arc-Standard Spinal Parsing with Stack-{LSTM}s",
author = "Ballesteros, Miguel and
Carreras, Xavier",
editor = "Miyao, Yusuke and
Sagae, Kenji",
booktitle = "Proceedings of the 15th International Conference on Parsing Technologies",
month = sep,
year = "2017",
address = "Pisa, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-6316",
pages = "115--121",
abstract = "We present a neural transition-based parser for spinal trees, a dependency representation of constituent trees. The parser uses Stack-LSTMs that compose constituent nodes with dependency-based derivations. In experiments, we show that this model adapts to different styles of dependency relations, but this choice has little effect for predicting constituent structure, suggesting that LSTMs induce useful states by themselves.",
}
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%0 Conference Proceedings
%T Arc-Standard Spinal Parsing with Stack-LSTMs
%A Ballesteros, Miguel
%A Carreras, Xavier
%Y Miyao, Yusuke
%Y Sagae, Kenji
%S Proceedings of the 15th International Conference on Parsing Technologies
%D 2017
%8 September
%I Association for Computational Linguistics
%C Pisa, Italy
%F ballesteros-carreras-2017-arc
%X We present a neural transition-based parser for spinal trees, a dependency representation of constituent trees. The parser uses Stack-LSTMs that compose constituent nodes with dependency-based derivations. In experiments, we show that this model adapts to different styles of dependency relations, but this choice has little effect for predicting constituent structure, suggesting that LSTMs induce useful states by themselves.
%U https://aclanthology.org/W17-6316
%P 115-121
Markdown (Informal)
[Arc-Standard Spinal Parsing with Stack-LSTMs](https://aclanthology.org/W17-6316) (Ballesteros & Carreras, IWPT 2017)
ACL
- Miguel Ballesteros and Xavier Carreras. 2017. Arc-Standard Spinal Parsing with Stack-LSTMs. In Proceedings of the 15th International Conference on Parsing Technologies, pages 115–121, Pisa, Italy. Association for Computational Linguistics.