Improved parsing for argument-clusters coordination

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Abstract

Syntactic parsers perform poorly in prediction of Argument-Cluster Coordination (ACC).We change the PTB representation of ACC to be more suitable for learning by a statistical PCFG parser, affecting 125 trees in the training set. Training on the modified trees yields a slight improvement in EVALB scores on sections 22 and 23. The main evaluation is on a corpus of 4th grade science exams, in which ACC structures are prevalent. On this corpus, we obtain an impressive ×2.7 improvement in recovering ACC structures compared to a parser trained on the original PTB trees.

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Ficler, J., & Goldberg, Y. (2016). Improved parsing for argument-clusters coordination. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers (pp. 72–76). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p16-2012

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