Abstract
This paper describes features and outcomes of the Named Entity Recognition on Transcribed Broadcast News task at EVALITA 2011. This task represented a change with respect to previous editions of the NER task within the EVALITA evaluation campaign because it was based on automatic transcription of spoken broadcast news. In this paper, we present the training and test data used, the evaluation procedure and participants' results. In particular, three participating systems are described and the results they obtained are discussed; special attention is given to the analysis of the impact of transcription errors on NER performance. © Springer-Verlag Berlin Heidelberg 2013.
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Lenzi, V. B., Speranza, M., & Sprugnoli, R. (2013). Named entity recognition on transcribed broadcast news at EVALITA 2011. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7689 LNAI, pp. 86–97). https://doi.org/10.1007/978-3-642-35828-9_10
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