Czech Named Entity Corpus and SVM-based Recognizer

This paper deals with recognition of named entities in Czech texts. We present a recently released corpus of Czech sen-tences with manually annotated named en-tities, in which a rich two-level classifica-tion scheme was used. There are around 6000 sentences in the corpus with roughly 33000marked named entity instances. We use the data for training and evaluating a named entity recognizer based on Support Vector Machine classification technique. The presented recognizer outperforms the results previously reported for NE recog-nition in Czech