On the shortfalls of Knowledge Graphs

I find this article explains some of the issues with KG, and especially
using
KGs as sole KR methods

https://www.aclweb.org/anthology/D17-1184
  Unfortunately, information extraction approaches for KG construction must
overcome complex, unreliable, and incomplete data. Many machine learning
methods have been proposed to address the challenge of cleaning and
completing KGs. One popular class of methods learn embeddings that
translate entities and relationships into a latent subspace, then use this
latent representation to derive additional, unobserved facts and score
existing facts (Bordes et al., 2013; Wang et al., 2014; Lin et al., 2015)