  The Digital Corpus of Sanskrit records around 650,000 sentences along with
their morphological and lexical tagging. But inconsistencies in morphological
analysis, and in providing crucial information like the segmented word, urges
the need for standardization and validation of this corpus. Automating the
validation process requires efficient analyzers which also provide the missing
information. The Sanskrit Heritage Engine's Reader produces all possible
segmentations with morphological and lexical analyses. Aligning these systems
would help us in recording the linguistic differences, which can be used to
update these systems to produce standardized results and will also provide a
Gold corpus tagged with complete morphological and lexical information along
with the segmented words. Krishna et al. (2017) aligned 115,000 sentences,
considering some of the linguistic differences. As both these systems have
evolved significantly, the alignment is done again considering all the
remaining linguistic differences between these systems. This paper describes
the modified alignment process in detail and records the additional linguistic
differences observed.
  Reference: Amrith Krishna, Pavankumar Satuluri, and Pawan Goyal. 2017. A
dataset for Sanskrit word segmentation. In Proceedings of the Joint SIGHUM
Workshop on Computational Linguistics for Cultural Heritage, Social Sciences,
Humanities and Literature, page 105-114. Association for Computational
Linguistics, August.
