Abstract
We present a new named entity recognizer for the Czech language. It reaches 82.82 F-measure on the Czech Named Entity Corpus 1.0 and significantly outperforms previously published Czech named entity recognizers. On the English CoNLL-2003 shared task, we achieved 89.16 F-measure, reaching comparable results to the English state of the art. The recognizer is based on Maximum Entropy Markov Model and a Viterbi algorithm decodes an optimal sequence labeling using probabilities estimated by a maximum entropy classifier. The classification features utilize morphological analysis, two-stage prediction, word clustering and gazetteers.
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Straková, J., Straka, M., Hajič, J. (2013). A New State-of-The-Art Czech Named Entity Recognizer. In: Habernal, I., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2013. Lecture Notes in Computer Science(), vol 8082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40585-3_10
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DOI: https://doi.org/10.1007/978-3-642-40585-3_10
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