Computational Linguistics
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
NameIt: Extraction of product names
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Market intelligence: linked data-driven entity resolution for customer and competitor analysis
ICWE'13 Proceedings of the 13th international conference on Web Engineering
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This paper presents an approach for predicting context sensitive entities exemplified in the domain of person names. Our approach is based on building a weighted context but also a weighted people graph and predicting the context entity by extracting the best fitting sub graph using a spreading activation technique. The results of the experiments show a quite promising F-Measure of 0.99.