TY - JOUR
T1 - Evaluating entity linking with wikipedia
AU - Hachey, Ben
AU - Radford, Will
AU - Nothman, Joel
AU - Honnibal, Matthew
AU - Curran, James R.
PY - 2013/1
Y1 - 2013/1
N2 - Named Entity Linking (nel) grounds entity mentions to their corresponding node in a Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity mentions in text to Wikipedia pages. Such systems typically search for candidate entities and then disambiguate them, returning either the best candidate or nil. However, comparison has focused on disambiguation accuracy, making it difficult to determine how search impacts performance. Furthermore, important approaches from the literature have not been systematically compared on standard data sets. We reimplement three seminal nel systems and present a detailed evaluation of search strategies. Our experiments find that coreference and acronym handling lead to substantial improvement, and search strategies account for much of the variation between systems. This is an interesting finding, because these aspects of the problem have often been neglected in the literature, which has focused largely on complex candidate ranking algorithms.
AB - Named Entity Linking (nel) grounds entity mentions to their corresponding node in a Knowledge Base (kb). Recently, a number of systems have been proposed for linking entity mentions in text to Wikipedia pages. Such systems typically search for candidate entities and then disambiguate them, returning either the best candidate or nil. However, comparison has focused on disambiguation accuracy, making it difficult to determine how search impacts performance. Furthermore, important approaches from the literature have not been systematically compared on standard data sets. We reimplement three seminal nel systems and present a detailed evaluation of search strategies. Our experiments find that coreference and acronym handling lead to substantial improvement, and search strategies account for much of the variation between systems. This is an interesting finding, because these aspects of the problem have often been neglected in the literature, which has focused largely on complex candidate ranking algorithms.
KW - Disambiguation
KW - Information extraction
KW - Named Entity Linking
KW - Semi-structured resources
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84870298772&partnerID=8YFLogxK
U2 - 10.1016/j.artint.2012.04.005
DO - 10.1016/j.artint.2012.04.005
M3 - Article
VL - 194
SP - 130
EP - 150
JO - Artificial Intelligence
JF - Artificial Intelligence
SN - 0004-3702
ER -