  This paper presents our recent developments in the automatic processing of
sign language corpora using the Hamburg Sign Language Annotation System
(HamNoSys). We designed an automated tool to convert HamNoSys annotations into
numerical labels for defined initial features of body and hand positions. Our
proposed numerical multilabels greatly simplify annotations' structure without
significant loss of gloss meaning. These numerical multilabels can potentially
be used to feed the machine learning models, which would accelerate the
development of vision-based sign language recognition. In addition, this tool
can assist experts in the annotation process and help identify semantic errors.
The code and sample annotations are publicly available at
\url{https://github.com/hearai/parse-hamnosys}.
