Wikipedia Search as Effective Entity Linking Algorithm

This paper reports on the participation of the LKD team in the English entity linking task at the TAC KBP 2013. We evaluated various modifications and combinations of the MostFrequent-Sense (MFS) based linking, the Entity Co-occurrence based linking (ECC), and the Explicit Semantic Analysis (ESA) based linking. We employed two our Wikipediabased NER systems, the Entityclassifier.eu and the SemiTags. Additionally, two Lucenebased entity linking systems were developed. For the competition we submitted 9 submissions in total, from which 5 used the textual context of the entities, and 4 submissions did not. Surprisingly, the MFS method based on the Wikipedia Search has proved to be the most effective approach – it achieved the best 0.555 B3+ F1 score from all our submissions and it achieved high 0.677 B3+ F1 score for Geo-Political (GPE) entities. In addition, the ESA based method achieved best 0.483 B3+ F1 for Organization (ORG) entities.