SlowGuess/NAACL_2021_OCR huggingface dataset:
Yu Zhang, Houquan Zhou, and Zhenghua Li. 2020. Fast and accurate neural crf constituency parsing. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, pages 4046-4053. International Joint Conferences on Artificial Intelligence Organization. Main track.
Yanpeng Zhao and Ivan Titov. 2020. Visually grounded compound PCFGs. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 4369-4379, Online. Association for Computational Linguistics.
Yanpeng Zhao and Ivan Titov. 2021. An empirical study of compound pcfgs. arXiv preprint arXiv:2103.02298.
Yanpeng Zhao, Liwen Zhang, and Kewei Tu. 2018. Gaussian mixture latent vector grammars. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1181-1189, Melbourne, Australia. Association for Computational Linguistics.
Hao Zhu, Yonatan Bisk, and Graham Neubig. 2020. The return of lexical dependencies: Neural lexicalized pcfgs. CoRR, abs/2007.15135.
To evaluate whether the nonterminals of trained models capture meaningful constituent clusters, we predict the unlabeled parse trees in the test set using MBR decoding, then choose the correctly predicted constituents and assign the maximum a posteriori (MAP) nonterminal symbols to them. Table 5 lists some representative nonterminals and their example constituents.
Table 5: Nonterminals and the corresponding example constituents.