Towards a Swahili Universal Dependency Treebank: Leveraging the Annotations of the Helsinki Corpus of Swahili

Abstract

Dependency annotation can be a laborious process for under-resourced languages. However, in some cases, other resources are available. We investigate whether we can leverage such resources in the case of Swahili: We use the annotations of the Helsinki Corpus of Swahili for creating a Universal Dependency treebank for Swahili. The Helsinki Corpus of Swahili provides word-level annotations for part of speech tags, morphological features, and functional syntactic tags. We train neural taggers for these types of annotations, then use those models to annotate our target corpus, the Swahili portion of the Global Voices Corpus. Based on the word-level annotations, we then manually create constraint grammar rules to annotate the target corpus for Universal Dependencies. In this paper, we describe the process, discuss the annotation decisions we had to make, and we evaluate the approach.