NERosetta for the Named Entity Multi-lingual Space

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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