@inproceedings{bjerva-etal-2016-semantic,
title = "Semantic Tagging with Deep Residual Networks",
author = "Bjerva, Johannes and
Plank, Barbara and
Bos, Johan",
editor = "Matsumoto, Yuji and
Prasad, Rashmi",
booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
month = dec,
year = "2016",
address = "Osaka, Japan",
publisher = "The COLING 2016 Organizing Committee",
url = "https://aclanthology.org/C16-1333",
pages = "3531--3541",
abstract = "We propose a novel semantic tagging task, semtagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations, and includes a novel residual bypass architecture. We evaluate the tagset both intrinsically on the new task of semantic tagging, as well as on Part-of-Speech (POS) tagging. Our system, consisting of a ResNet and an auxiliary loss function predicting our semantic tags, significantly outperforms prior results on English Universal Dependencies POS tagging (95.71{\%} accuracy on UD v1.2 and 95.67{\%} accuracy on UD v1.3).",
}
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%0 Conference Proceedings
%T Semantic Tagging with Deep Residual Networks
%A Bjerva, Johannes
%A Plank, Barbara
%A Bos, Johan
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F bjerva-etal-2016-semantic
%X We propose a novel semantic tagging task, semtagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations, and includes a novel residual bypass architecture. We evaluate the tagset both intrinsically on the new task of semantic tagging, as well as on Part-of-Speech (POS) tagging. Our system, consisting of a ResNet and an auxiliary loss function predicting our semantic tags, significantly outperforms prior results on English Universal Dependencies POS tagging (95.71% accuracy on UD v1.2 and 95.67% accuracy on UD v1.3).
%U https://aclanthology.org/C16-1333
%P 3531-3541
Markdown (Informal)
[Semantic Tagging with Deep Residual Networks](https://aclanthology.org/C16-1333) (Bjerva et al., COLING 2016)
ACL
- Johannes Bjerva, Barbara Plank, and Johan Bos. 2016. Semantic Tagging with Deep Residual Networks. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 3531–3541, Osaka, Japan. The COLING 2016 Organizing Committee.