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Aug, 2017
派生形态的范式完成
Paradigm Completion for Derivational Morphology
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Ryan Cotterell, Ekaterina Vylomova, Huda Khayrallah, Christo Kirov, David Yarowsky
TL;DR
本研究应用神经序列到序列模型解决NLP中复杂词形派生问题,并介绍派生范式完成任务。基于优于非神经基准线16.4%的结果,我们的神经模型学会了各种派生模式。但是,由于派生性构词涉及语义、历史和词汇考虑,因此未来需要更多工作来实现和生成机制的性能平衡。
Abstract
The generation of complex derived word forms has been an overlooked problem in
nlp
; we fill this gap by applying
neural sequence-to-sequence models
to the task. We overview the theoretical motivation for a
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