Chinese preposition selection for grammatical error diagnosis
Journal
26th International Conference on Computational Linguistics
Pages
888-899
ISBN
9784879747020
Date Issued
2016
Author(s)
Abstract
Misuse of Chinese prepositions is one of common word usage errors in grammatical error diagnosis. In this paper, we adopt the Chinese Gigaword corpus and HSK corpus as L1 and L2 corpora, respectively. We explore gated recurrent neural network model (GRU), and an ensemble of GRU model and maximum entropy language model (GRU-ME) to select the best preposition from 43 candidates for each test sentence. The experimental results show the advantage of the GRU models over simple RNN and n-gram models. We further analyze the effectiveness of linguistic information such as word boundary and part-of-speech tag in this task. ? 1963-2018 ACL.
Type
conference paper