We develop a new neural RE method REDS2 in the multi-instance learning paradigm which fuses information from 1-hop DS and 2-hop DS using a hierarchical model structure, and substantially outperforms existing RE methods on a benchmark dataset.
• Sentence Encoding: For each sentence s in bag S h,t or S T h,t , a sentence encoder is used to obtain its semantic representation s. • Hierarchical Bag Aggregation: Once the embedding of each sentence is learned, we first use a sentence-level attention mechanism to get bag representation h and h T , and then aggregate them for final relation prediction.