Comparing the results of LSTM+PAR+FEAT to LSTM+PAR and LSTM+PAR+FEAT−wordEmb, it seems that word embeddings and the small set of simple features (most of them are capturing the surface and syntactic properties of mentions) are complementary.
mediated/function and mediated/bridging benefit most from word embeddings which provide useful semantic knowledge to capture these two categories.