Investigating the Morphological Complexity of German Named Entities: The Case of the GermEval NER Challenge
B. Klimek, M. Ackermann, A. Kirschenbaum, and S. Hellmann. Proceedings of the International Conference of the German Society for Computational Linguistics and Language Technology, German Society for Computational Linguistics and Language Technology, (2017)
This paper presents a detailed analysis of Named Entity Recognition (NER) in German, based on the performance of systems that participated in the GermEval 2014 shared task. It focuses on the role of morphology in named entities, an issue too often neglected in the NER task. We introduce a measure to characterize the morphological complexity of German named entities and apply it to the subset of named entities identified by all systems, and to the subset of named entities none of the systems recognized. We discover that morphologically complex named entities are more prevalent in the latter set than in the former, a finding which should be taken into account in future development of methods of that sort. In addition, we provide an analysis of issues found in the GermEval gold standard annotation, which affected also the performance measurements of the different systems.