UD Annotatrix: An Annotation Tool For Universal Dependencies

In this paper we introduce the UD Annotatrix annotation tool for manual annotation of Universal Dependencies. This tool has been designed with the aim that it should be tailored to the needs of the Universal Dependencies (UD) community, including that it should operate in fully-offline mode, and is freely-available under the GNU GPL licence. In this paper, we provide some background to the tool, an overview of its development, and background on how it works. We compare it with some other widely-used tools which are used for Universal Dependencies annotation, describe some features unique to UD Annotatrix, and finally outline some avenues for future work and provide a few concluding remarks

Universal Dependencies Parsing for Colloquial Singaporean English

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.Comment: Accepted by ACL 201