Istituto di Scienza e Tecnologie dell'Informazione     
Berardi G., Attardi G., Dei Rossi S., Simi M. The Tanl tagger for named entity recognition on transcribed broadcast news at Evalita 2011. Bernardo Magnini, Francesco Cutugno, Mauro Falcone, Emanuele Pianta (eds.). (Lecture Notes in Computer Science, vol. 7689). Roma: Springer, 2013.
The Tanl tagger is a configurable tagger based on a Maximum Entropy classifier, which uses dynamic programming to select the best sequences of tags. We applied it to the NER tagging task, customizing the set of features to use, and including features deriving from dictionaries extracted from the training corpus. The final accuracy of the tagger is further improved by applying simple heuristic rules.
URL: http://link.springer.com/chapter/10.1007/978-3-642-35828-9_13
DOI: 10.1007/978-3-642-35828-9_13
Subject Named Entity Recognition
Maximum Entropy
Dynamic programming
H.3.1 Content Analysis and Indexing. Linguistic processing
68T50 Natural language processing

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