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        <title>An Empirical Study of Building a Strong Baseline for Constituency Parsing</title>
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    <abstract>This paper investigates the construction of a strong baseline based on general purpose sequence-to-sequence models for constituency parsing. We incorporate several techniques that were mainly developed in natural language generation tasks, e.g., machine translation and summarization, and demonstrate that the sequence-to-sequence model achieves the current top-notch parsers’ performance (almost) without requiring any explicit task-specific knowledge or architecture of constituent parsing.</abstract>
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%0 Conference Proceedings
%T An Empirical Study of Building a Strong Baseline for Constituency Parsing
%A Suzuki, Jun
%A Takase, Sho
%A Kamigaito, Hidetaka
%A Morishita, Makoto
%A Nagata, Masaaki
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F suzuki-etal-2018-empirical
%X This paper investigates the construction of a strong baseline based on general purpose sequence-to-sequence models for constituency parsing. We incorporate several techniques that were mainly developed in natural language generation tasks, e.g., machine translation and summarization, and demonstrate that the sequence-to-sequence model achieves the current top-notch parsers’ performance (almost) without requiring any explicit task-specific knowledge or architecture of constituent parsing.
%R 10.18653/v1/P18-2097
%U https://aclanthology.org/P18-2097
%U https://doi.org/10.18653/v1/P18-2097
%P 612-618

Markdown (Informal)

[An Empirical Study of Building a Strong Baseline for Constituency Parsing](https://aclanthology.org/P18-2097) (Suzuki et al., ACL 2018)

• An Empirical Study of Building a Strong Baseline for Constituency Parsing (Suzuki et al., ACL 2018)

ACL

• Jun Suzuki, Sho Takase, Hidetaka Kamigaito, Makoto Morishita, and Masaaki Nagata. 2018. An Empirical Study of Building a Strong Baseline for Constituency Parsing. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 612–618, Melbourne, Australia. Association for Computational Linguistics.