Abstract
Named Entity Recognition has been a hot topic in Natural Language Processing for more than fifteen years. A number of systems for various languages have been developed using different approaches and based on different named entity schemes and tagging strategies. We present the NERosetta web application that can be used for comparison of these various approaches applied to aligned texts (bitexts). In order to illustrate its functionalities, we have used one literary text, its 7 bitexts involving 5 languages and 5 different NER systems. We present some preliminary results and give guidelines for further development.
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A tool developed by P. Bonhomme, T. M. H. Nguyen and S. O’Rourke, http://led.loria.fr/outils/ALIGN/align.html.
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We have used the version of the cascade and e-dictionaries from February 2012.
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This research was conducted through the project 178006 financed by the Serbian Ministry of Education, Science and Technological Development.
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Krstev, C., Zečević, A., Vitas, D., Kyriacopoulou, T. (2016). NERosetta for the Named Entity Multi-lingual Space. In: Vetulani, Z., Uszkoreit, H., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2013. Lecture Notes in Computer Science(), vol 9561. Springer, Cham. https://doi.org/10.1007/978-3-319-43808-5_25
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