Morphological Analysis Corpus Construction of Uyghur

Abstract

Morphological analysis is a fundamental task in natural language processing, and results can be applied to different downstream tasks such as named entity recognition, syntactic analysis, and machine translation. However, there are many problems in morphological analysis, such as low accuracy caused by a lack of resources. In this paper, to alleviate the lack of resources in Uyghur morphological analysis research, we construct a Uyghur morphological analysis corpus based on the analysis of grammatical features and the format of the general morphological analysis corpus. We define morphological tags from 14 dimensions and 53 features, manually annotate and correct the dataset. Finally, the corpus provided some informations such as word, lemma, part of speech, morphological analysis tags, morphological segmentation, and lemmatization. Also, this paper analyzes some basic features of the corpus, and we use the models and datasets provided by SIGMORPHON Shared Task organizers to design comparative experiments to verify the corpus’s availability. Results of the experiment are 85.56%, 88.29%, respectively. The corpus provides a reference value for morphological analysis and promotes the research of Uyghur natural language processing.