Learning to map dependency parses to abstract meaning representations

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Abstract

Meaning Representation (AMR) is a semantic representation language used to capture the meaning of English sentences. In this work, we propose an AMR parser based on dependency parse rewrite rules. This approach transfers dependency parses into AMRs by integrating the syntactic dependencies, semantic arguments, named entity and co-reference information. A dependency parse to AMR graph aligner is also introduced as a preliminary step for designing the parser.

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APA

Chen, W. T. (2015). Learning to map dependency parses to abstract meaning representations. In ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, Proceedings of the Student Research Workshop (pp. 41–46). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p15-3007

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