Snorkel has a label mutual exclusion assumption right? My core problem is a multi-label problem, but my snorkel data, from the LabelModel is inherently single-

Snorkel has a label mutual exclusion assumption right? My core problem is a multi-label problem, but my snorkel data, from the LabelModel is inherently single-label (mutually exclusive). What is the prevailing recommendation to do multi-label w/ Snorkel? Is the below what you are currently recommending? For a given, k-wise multi-label problem: 1. Generate k binary datasets w/ LabelModel 2. Train k separate binary classifiers for each respective dataset 3. At inference/prediction time pass input though the k classifiers and get scores. Is this what the current recommendation is? Create a set of binary classifiers?