@inproceedings{ye-etal-2018-language,
title = "Language Generation via {DAG} Transduction",
author = "Ye, Yajie and
Sun, Weiwei and
Wan, Xiaojun",
editor = "Gurevych, Iryna and
Miyao, Yusuke",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2018",
address = "Melbourne, Australia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P18-1179",
doi = "10.18653/v1/P18-1179",
pages = "1928--1937",
abstract = "A DAG automaton is a formal device for manipulating graphs. By augmenting a DAG automaton with transduction rules, a DAG transducer has potential applications in fundamental NLP tasks. In this paper, we propose a novel DAG transducer to perform graph-to-program transformation. The target structure of our transducer is a program licensed by a declarative programming language rather than linguistic structures. By executing such a program, we can easily get a surface string. Our transducer is designed especially for natural language generation (NLG) from type-logical semantic graphs. Taking Elementary Dependency Structures, a format of English Resource Semantics, as input, our NLG system achieves a BLEU-4 score of 68.07. This remarkable result demonstrates the feasibility of applying a DAG transducer to resolve NLG, as well as the effectiveness of our design.",
}
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%0 Conference Proceedings
%T Language Generation via DAG Transduction
%A Ye, Yajie
%A Sun, Weiwei
%A Wan, Xiaojun
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F ye-etal-2018-language
%X A DAG automaton is a formal device for manipulating graphs. By augmenting a DAG automaton with transduction rules, a DAG transducer has potential applications in fundamental NLP tasks. In this paper, we propose a novel DAG transducer to perform graph-to-program transformation. The target structure of our transducer is a program licensed by a declarative programming language rather than linguistic structures. By executing such a program, we can easily get a surface string. Our transducer is designed especially for natural language generation (NLG) from type-logical semantic graphs. Taking Elementary Dependency Structures, a format of English Resource Semantics, as input, our NLG system achieves a BLEU-4 score of 68.07. This remarkable result demonstrates the feasibility of applying a DAG transducer to resolve NLG, as well as the effectiveness of our design.
%R 10.18653/v1/P18-1179
%U https://aclanthology.org/P18-1179
%U https://doi.org/10.18653/v1/P18-1179
%P 1928-1937
Markdown (Informal)
[Language Generation via DAG Transduction](https://aclanthology.org/P18-1179) (Ye et al., ACL 2018)
ACL
- Yajie Ye, Weiwei Sun, and Xiaojun Wan. 2018. Language Generation via DAG Transduction. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1928–1937, Melbourne, Australia. Association for Computational Linguistics.