  We report an evaluation of the effectiveness of the existing knowledge base
embedding models for relation prediction and for relation extraction on a wide
range of benchmarks. We also describe a new benchmark, which is much larger and
complex than previous ones, which we introduce to help validate the
effectiveness of both tasks. The results demonstrate that knowledge base
embedding models are generally effective for relation prediction but unable to
give improvements for the state-of-art neural relation extraction model with
the existing strategies, while pointing limitations of existing methods.
