MT-Path predicts missing entities in N-tuple temporal knowledge graphs by training a mixture of three reinforcement-learning path-finding policies (predicate, core-element, whole-fact) with an auxiliary-aware GCN, and reports state-of-the-art results on NICE and NWIKI.
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Mixture Policy based Multi-Hop Reasoning over N-tuple Temporal Knowledge Graphs
MT-Path predicts missing entities in N-tuple temporal knowledge graphs by training a mixture of three reinforcement-learning path-finding policies (predicate, core-element, whole-fact) with an auxiliary-aware GCN, and reports state-of-the-art results on NICE and NWIKI.