Likewise, the MANUAL dataset had many concepts that were not in the training data for MTransE, which seriously degraded its performance.
conceptNet (Liu and Singh, 2004b;Speer et al., 2017) adopted natural language expressions such as words and phrases that may have ambiguities to represent knowledge, which made it possible to collect millions of commonsense facts in multiple languages via crowdsourcing.