Multi-layer Annotation of the Rgveda

The paper introduces a multi-level annotation of the RGVEDA, a fundamental Sanskrit text composed in the 2. millenium BCE that is important for South-Asian and Indo-European linguistics, as well as Cultural Studies. We describe the individual annotation levels, including phonetics, morphology, lexicon, and syntax, and show how these different levels of annotation are merged to create a novel annotated corpus of Vedic Sanskrit. Vedic Sanskrit is a complex, but computationally under-resourced language. Therefore, creating this resource required considerable domain adaptation of existing computational tools, which is discussed in this paper. Because parts of the annotations are selective, we propose a bi-directional LSTM based sequential model to supplement missing verb-argument links.