On the Temporality of Priors in Entity Linking

TL;DR

This paper investigates how the temporal aspect of prior probabilities influences the performance of entity linking systems, highlighting the importance of considering time in modeling mention-to-entity priors.

Contribution

It introduces a systematic study of the temporality of priors in entity linking, emphasizing the need to incorporate temporal dynamics for improved accuracy.

Findings

Temporal priors significantly impact linking accuracy

Performance varies with the temporal validity of texts and KBs

Highlighting the importance of temporal modeling in entity linking

Abstract

Entity linking is a fundamental task in natural language processing which deals with the lexical ambiguity in texts. An important component in entity linking approaches is the mention-to-entity prior probability. Even though there is a large number of works in entity linking, the existing approaches do not explicitly consider the time aspect, specifically the temporality of an entity's prior probability. We posit that this prior probability is temporal in nature and affects the performance of entity linking systems. In this paper we systematically study the effect of the prior on the entity linking performance over the temporal validity of both texts and KBs.