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This paper is concerned with structured machine learning, in a supervisedmachine learning context. It discusses how to make joint structured learning oninterdependent objects of different nature, as well as how to enforce logicalcon-straints when predicting labels. We explain how this need arose in aDocument Understanding task. We then discuss a general extension to ConditionalRandom Field (CRF) for this purpose and present the contributed open sourceimplementation on top of the open source PyStruct library. We evaluate itsperformance on a publicly available dataset.

Joint Structured Learning and Predictions under Logical Constraints in Conditional Random Fields