Memory-based named entity recognition in tweets
InCeur Workshop Proceedings, (2013)Cano, A.; Rowe, M.; Stankovic, M. (ed.), #MSM2013 Workshop Concept Extraction Challenge Proceedings, pp. 40-43
Concept Extraction Challenge at Making Sense of Microposts 2013
Article in monograph or in proceedings
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Communicatie- en informatiewetenschappen
Ceur Workshop Proceedings
Cano, A.; Rowe, M.; Stankovic, M. (ed.), #MSM2013 Workshop Concept Extraction Challenge Proceedings
SubjectCEUR Workshop proceedings; ADNEXT (Adaptive Information Extraction over Time); Language & Speech Technology; Language in Society; Nederlab
We present a memory-based named entity recognition system that participated in the MSM-2013 Concept Extraction Challenge. The system expands the training set of annotated tweets with part-of-speech tags and seedlist information, and then generates a sequential memory-based tagger comprised of separate modules for known and unknown words. Two taggers are trained: one on the original capitalized data, and one on a lowercased version of the training data. The intersection of named entities in the predictions of the two taggers is kept as the final output.
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