We present a machine learning-based method for jointly labeling POS tags and named entities. This joint labeling is performed by utilizing factor graphs. The variables of part of speech and named entity labels are connected by factors so the tagger jointly determines the best labeling for the two labeling tasks. Using the feature sets of SZTENER and the POS-tagger magyarlanc, we built a model that is able to outperform both of the original taggers. © 2012 Springer-Verlag.
CITATION STYLE
Móra, G., & Vincze, V. (2012). Joint part-of-speech tagging and named entity recognition using factor graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7499 LNAI, pp. 232–239). https://doi.org/10.1007/978-3-642-32790-2_28
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