Named Entity Recognition for Highly Inflectional Languages: Effects of Various Lemmatization and Stemming Approaches
作者： Michal Konkol , Miloslav Konopík
DOI: 10.1007/978-3-319-10816-2_33
关键词:
摘要: In this paper, we study the effects of various lemmatization and stemming approaches on named entity recognition (NER) task for Czech, a highly inflectional language. Lemmatizers are seen as necessary component Czech NER systems they were used in all published papers about so far. Thus, it has an utmost importance to explore their benefits, limits differences between simple complex methods. Our experiments evaluated standard Named Entity Corpus 1.1 well newly created 2.0 version.
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