Our work is also related to the domain of question answering and reasoning in knowledge graphs (Das et al., 2018;Xiong et al., 2018;Hamilton et al., 2018;Xiong et al., 2017;Welbl et al., 2018;Kartsaklis et al., 2018), where either the model is provided with a knowledge graph to perform inference over or where the model must infer a knowledge graph from the text itself.
our benchmark suite-termed CLUTRR (Compositional Language Understanding and Text-based Relational Reasoning)-contains a large set of semi-synthetic stories involving hypothetical families.