Abstract
In the named entity normalization task, a system identifies a canonical unambiguous referent for names like Bush or Alabama. Resolving synonymy and ambiguity of such names can benefit end-to-end information access tasks. We evaluate two entity normalization methods based on Wikipedia in the context of both passage and document retrieval for question anwering. We find that even a simple normalization method leads to improvements of early precision, both for document and passage retrieval. Moreover, better normalization results in better retrieval performance.
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Khalid, M.A., Jijkoun, V., de Rijke, M. (2008). The Impact of Named Entity Normalization on Information Retrieval for Question Answering. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_83
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DOI: https://doi.org/10.1007/978-3-540-78646-7_83
Publisher Name: Springer, Berlin, Heidelberg
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