On the Temporality of Priors in Entity Linking
Computation and Language
2021-01-15 v1 Machine Learning
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.
Keywords
Cite
@article{arxiv.2101.05593,
title = {On the Temporality of Priors in Entity Linking},
author = {Renato Stoffalette Joao},
journal= {arXiv preprint arXiv:2101.05593},
year = {2021}
}