I liked the focus paper a lot.
My paper was "Joint entity and relation extraction using Card-Pyramid Parsing" by Kate and Mooney (CoNLL 2010). They place a "pyramid" structure over the chunks of a sentence, where the nodes are possible relations that could hold between pairs of chunks. (Like a CKY chart. But the semantics are supposed to be, a node refers to the leaves of its span endpoints... I think.) There are productions for e.g. how relations are composed of entity types. I had a hard time telling if the goal is to create a single coherent tree, exactly. They do a parse using classifiers for entity and relation recognition as features for parse decisions (Nivre-like, kind of). They have results show the joint inference sometimes improves performance. But I was still confused by the motivation of their approach, beyond joint inference (for which one can imagine many other reasonable approaches).