Abstract meaning representation for legal documents: an empirical research on a human-annotated dataset

Author:

Vu Sinh Trong,Le Nguyen Minh,Satoh Ken

Funder

JST CREST Grant

Publisher

Springer Science and Business Media LLC

Subject

Law,Artificial Intelligence

Reference53 articles.

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2. Ballesteros M, Al-Onaizan Y (2017) AMR parsing using stack-LSTMs. In: Proceedings of the 2017 conference on empirical methods in natural language processing, pp. 1269–1275. Association for Computational Linguistics, Copenhagen, Denmark. https://doi.org/10.18653/v1/D17-1130

3. Banarescu L, Bonial C, Cai S, Georgescu M, Griffitt K, Hermjakob U, Knight K, Koehn P, Palmer M, Schneider N (2013) Abstract meaning representation for sembanking. In: Proceedings of the 7th linguistic annotation workshop and interoperability with discourse, pp. 178–186. Association for Computational Linguistics, Sofia, Bulgaria

4. Basile V, Bos J, Evang K, Venhuizen N (2012) Developing a large semantically annotated corpus. In: Proceedings of the eighth international conference on language resources and evaluation (LREC’12), pp. 3196–3200. European Language Resources Association (ELRA), Istanbul, Turkey. http://www.lrec-conf.org/proceedings/lrec2012/pdf/534_Paper.pdf

5. Brandt L, Grimm D, Zhou M, Versley Y (2016) ICL-HD at SemEval-2016 task 8: meaning representation parsing-augmenting AMR parsing with a preposition semantic role labeling neural network. In: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016), pp. 1160–1166. Association for Computational Linguistics, San Diego, California. https://doi.org/10.18653/v1/S16-1179

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1. PAMR: Persian Abstract Meaning Representation Corpus;ACM Transactions on Asian and Low-Resource Language Information Processing;2024-03-09

2. Assessing the Cross-linguistic Utility of Abstract Meaning Representation;Computational Linguistics;2023-12-21

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