@inproceedings{huang-etal-2021-globally,
title = "A Globally Normalized Neural Model for Semantic Parsing",
author = {Huang, Chenyang and
Yang, Wei and
Cao, Yanshuai and
Za{\"\i}ane, Osmar and
Mou, Lili},
editor = "Kozareva, Zornitsa and
Ravi, Sujith and
Vlachos, Andreas and
Agrawal, Priyanka and
Martins, Andr{\'e}",
booktitle = "Proceedings of the 5th Workshop on Structured Prediction for NLP (SPNLP 2021)",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.spnlp-1.7",
doi = "10.18653/v1/2021.spnlp-1.7",
pages = "61--66",
abstract = "In this paper, we propose a globally normalized model for context-free grammar (CFG)-based semantic parsing. Instead of predicting a probability, our model predicts a real-valued score at each step and does not suffer from the label bias problem. Experiments show that our approach outperforms locally normalized models on small datasets, but it does not yield improvement on a large dataset.",
}
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%0 Conference Proceedings
%T A Globally Normalized Neural Model for Semantic Parsing
%A Huang, Chenyang
%A Yang, Wei
%A Cao, Yanshuai
%A Zaïane, Osmar
%A Mou, Lili
%Y Kozareva, Zornitsa
%Y Ravi, Sujith
%Y Vlachos, Andreas
%Y Agrawal, Priyanka
%Y Martins, André
%S Proceedings of the 5th Workshop on Structured Prediction for NLP (SPNLP 2021)
%D 2021
%8 August
%I Association for Computational Linguistics
%C Online
%F huang-etal-2021-globally
%X In this paper, we propose a globally normalized model for context-free grammar (CFG)-based semantic parsing. Instead of predicting a probability, our model predicts a real-valued score at each step and does not suffer from the label bias problem. Experiments show that our approach outperforms locally normalized models on small datasets, but it does not yield improvement on a large dataset.
%R 10.18653/v1/2021.spnlp-1.7
%U https://aclanthology.org/2021.spnlp-1.7
%U https://doi.org/10.18653/v1/2021.spnlp-1.7
%P 61-66
Markdown (Informal)
[A Globally Normalized Neural Model for Semantic Parsing](https://aclanthology.org/2021.spnlp-1.7) (Huang et al., spnlp 2021)
ACL
- Chenyang Huang, Wei Yang, Yanshuai Cao, Osmar Zaïane, and Lili Mou. 2021. A Globally Normalized Neural Model for Semantic Parsing. In Proceedings of the 5th Workshop on Structured Prediction for NLP (SPNLP 2021), pages 61–66, Online. Association for Computational Linguistics.