Trust, but Verify! Better Entity Linking through Automatic Verification

摘要

We introduce automatic verification as a post-processing step for entity linking (EL). The proposed method trusts EL sys tem results collectively, by assuming en tity mentions are mostly linked correctly, in order to create a semantic profile of the given text using geospatial and temporal information, as well as fine-grained entity types. This profile is then used to auto matically verify each linked mention indi vidually, i.e., to predict whether it has been linked correctly or not. Verification allows leveraging a rich set of global and pairwise features that would be prohibitively expen sive for EL systems employing global in ference. Evaluation shows consistent im provements across datasets and systems. In particular, when applied to state-of-the-art systems, our method yields an abso lute improvement in linking performance of up to 1.7 Fl on AIDA/CoNLL'03 and up to 2.4 Fl on the English TAC KBP 2015 TEDL dataset.