Entity Disambiguation Using a Markov-Logic Network

Entity linking (EL) is the task of linking a textual named entity mention to a knowledge base entry. It is a difficult task involving many challenges, but the most crucial problem is entity ambiguity. Traditional EL approaches usually employ different constraints and filtering techniques to improve performance. However, these constraints are executed in several different stages and cannot be used interactively. In this paper, we propose several disambiguation formulae/features and employ a Markov logic network to model interweaved constraints found in one type of EL, gene mention linking. To assess our systems effectiveness in different applications, we adopt two evaluation schemes: article-wide and instance-based precision/recall/F-measure. Experimental results show that our system outperforms the baseline systems and state-of-the-art systems under both evaluation schemes.