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arXiv · 1705.06463

Universal Dependencies Parsing for Colloquial Singaporean English

Hongmin Wang·Yue Zhang·GuangYong Leonard Chan·Jie Yang·Hai Leong Chieu
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Abstract

Singlish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We investigate dependency parsing of Singlish by constructing a dependency treebank under the Universal Dependencies scheme, and then training a neural network model by integrating English syntactic knowledge into a state-of-the-art parser trained on the Singlish treebank. Results show that English knowledge can lead to 25% relative error reduction, resulting in a parser of 84.47% accuracies. To the best of our knowledge, we are the first to use neural stacking to improve cross-lingual dependency parsing on low-resource languages. We make both our annotation and parser available for further research.

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Hongmin Wang, Yue Zhang, GuangYong Leonard Chan, Jie Yang, Hai Leong Chieu. 2017-05-18. Universal Dependencies Parsing for Colloquial Singaporean English. https://arxiv.org/abs/1705.06463

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