Abstract
Named entity recognition (NER) is used in many domains beyond the newswire text that comprises current gold-standard corpora. Recent work has used Wikipedia's link structure to automatically generate near gold-standard annotations. Until now, these resources have only been evaluated on newswire corpora or themselves. We present the first NER evaluation on a Wikipedia gold standard (WG) corpus. Our analysis of cross-corpus performance on WG shows that Wikipedia text may be a harder NER domain than newswire. We find that an automatic annotation of Wikipedia has high agreement with WG and, when used as training data, outperforms newswire models by up to 7.7%.
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CITATION STYLE
Balasuriya, D., Ringland, N., Nothman, J., Murphy, T., & Curran, J. R. (2009). Named entity recognition in Wikipedia. In People’s Web 2009 - 2009 Workshop on The People’s Web Meets NLP: Collaboratively Constructed Semantic Resources at the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, ACL-IJCNLP 2009 - Proceedings (pp. 10–18). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1699765.1699767
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