Cue-based assertion classification for Swedish clinical text--developing a lexicon for pyConTextSwe.OBJECTIVE
 In this paper, we continue our study of porting an assertion system (pyConTextNLP) from English to Swedish (pyConTextSwe) by creating an optimized assertion lexicon for clinical Swedish.


 We applied four assertion classes (definite existence, probable existence, probable negated existence and definite negated existence) and two binary classes (existence yes/no and uncertainty yes/no) to pyConTextSwe.  We compared pyConTextSwe's performance with and without the added cues on a development set, and improved the lexicon further after an error analysis.  Following integration steps, we added 454 cues to pyConTextSwe.  We have successfully ported pyConTextNLP to Swedish (pyConTextSwe). 
pyConTextSwe