Implementation of Croatian NERC System

In this paper a system for Named Entity Recognition and Classification in Croatian language is described. The system is composed of the module for sentence segmentation, inflectional lexicon of common words, inflectional lexicon of names and regular local grammars for automatic recognition of numerical and temporal expressions. After the first step (sentence segmentation), the system attaches to each token its full morphosyntactic description and appropriate lemma and additional tags for potential categories for names without disambiguation. The third step (the core of the system) is the application of a set of rules for recognition and classification of named entities in already annotated texts. Rules based on described strategies (like internal and external evidence) are applied in cascade of transducers in defined order. Although there are other classification systems for NEs, the results of our system are annotated NEs which are following MUC-7 specification. System is applied on informative and noninformative texts and results are compared. F-measure of the system applied on informative texts yields over 90%.