MuVER

Multi-View Entity Representations, or MuVER, is an approach for entity retrieval that constructs multi-view representations for entity descriptions and approximates the optimal view for mentions via a heuristic searching method. It matches a mention to the appropriate entity by comparing it with entity descriptions. Motivated by the fact that mentions with different contexts correspond to different parts in descriptions, multi-view representations are constructed for each description. Specifically, we segment a description into several sentences. We refer to each sentence as a view $v$, which contains partial information, to form a view set $\mathcal{V}$ of the entity $e$. The Figure illustrates an example that constructs a view set $\mathcal{V}$ for “Kobe Bryant”.