Domain-aware Evaluation of Named Entity Recognition Systems for Croatian
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| Title | Domain-aware Evaluation of Named Entity Recognition Systems for Croatian |
| Authors | |
| Abstract | We provide an evaluation of the currently available named entity recognition systems for Croatian. The evaluation puts special emphasis on domain dependence. To this goal, we manually annotated a dataset of approximately 1 million tokens of Croatian text from various domains within the newspaper text genre. The dataset was annotated using a three-class named entity tagset – denoting personal names, locations and organizations. We give insight to feature selection, domain sensitivity and effects of increase in training set size for statistical named entity recognition using the state-of-the-art Stanford NER system. We also sketch a comparison of publicly available named entity recognition systems for Croatian considering domain dependence, regardless of their underlying paradigms. Our top-performing system achieved an F1-score of 0.884 in a mixed-domain testing scenario, scoring 0.925 and 0.843 in the two domains separated for the experiment. The system shows consistency in state-of-the-art scores for detecting names of persons, locations and organizations. |
| Publisher | University of Zagreb, University Computing Centre - SRCE |
| Date | 2013-10-31 |
| Source | Journal of Computing and Information Technology Vol 21, No 3 (2013) |
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