基于IWCS的DRS解析共享任务中的神经拳击手

Rik van Noord
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引用次数: 6

摘要

本文描述了我们参与篇章表示结构解析的共享任务。它遵循Van Noord等人(2018)的工作,他们采用神经序列到序列模型来生成drs,也利用多个编码器的语言信息。我们对该模型的性能进行了详细的研究,并表明:(i)语言特征的好处在许多不同训练数据量的实验中是明显的,(ii)可以通过应用一些后处理方法来修复病态输出来改进模型。我们的模型以84.5的f分在比赛中获得第二名。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Boxer at the IWCS Shared Task on DRS Parsing
This paper describes our participation in the shared task of Discourse Representation Structure parsing. It follows the work of Van Noord et al. (2018), who employed a neural sequence-to-sequence model to produce DRSs, also exploiting linguistic information with multiple encoders. We provide a detailed look in the performance of this model and show that (i) the benefit of the linguistic features is evident across a number of experiments which vary the amount of training data and (ii) the model can be improved by applying a number of postprocessing methods to fix ill-formed output. Our model ended up in second place in the competition, with an F-score of 84.5.
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