We evaluate our models on the corpora of<cite> Stab and Gurevych (2016)</cite> and Peldszus (2014) , and compare our results with the results of the aformentioned authors. Our results show that (1) joint modeling is imperative for competitive performance on the link extraction task, (2) the presence of the second recurrence improves performance over a non-sequence-to-sequence model, and (3) the joint model can outperform models with heavy featureengineering and corpus-specific constraints.