Publication at Faculty of Mathematics and Physics |
2009
Abstract
This paper deals with recognition of named entities in Czech texts. We present a recently released corpus of Czech sentences with manually annotated named entities, in which a rich two-level classification scheme was used.
There are around 6000 sentences in the corpus with roughly 33000 marked 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 recognition in Czech.