This is because MAP is computed as the precision of all possible correct predictions in a ranked list, where precision is counted as 0 if the correct prediction is not included in the list.
there are many relation instances in our randomly selected test set that are not inferrable from the knowledge base, and the low recall hurts the MAP metric.