This paper describes the CatFormCompare tool, designed to enable the comparison of phonological content between pairs of signs, especially in larger datasets. With this tool and a schema for coding categorical form (the SL CatForm coding schema), a pipeline is created that allows a feedback mechanism for advancing research—specifically by directly addressing one of the hard problems in sign language phonology: how to extract true minimal pairs from datasets coded for categorical form? Solving this problem would simultaneously improve phonological distance measurements for sign languages because it would mean that the units for measuring distance are grounded in the linguistic structure of the language and not simply a by-product of the coding system. Here we report on the tool and the first evaluation of its functioning.

Over the past six decades, a variety of systems have been developed for representing sign language forms, from Stokoe Notation (Stokoe, 1960) to SignWriting (Sutton, 1999) and lexical database schemas. Each was designed with specific goals and applications, leading to a fragmented landscape of representations. To enable greater interoperability and data sharing among sign language users and researchers, we propose a robust approach to translating between notation systems. As a first step in this direction, we introduce a formal mapping framework between HamNoSys and the SL CatForm coding schema, describe its implementation, and present empirical evidence of its performance. An extensive evaluation of mapping mismatches revealed improvements to the mapping logic needed to further advance the HNS2CF mapping tool. However, the initial version of the system already achieves an overall accuracy of 76.7% and an in-depth analysis reveals that many apparent mismatches stem from annotator disagreement rather than mapping errors, indicating that the tool’s actual accuracy is even higher. These results demonstrate the feasibility and promise of establishing mapping mechanisms across sign representation systems.