Abstract
This paper proposes a method for Named Entity (NE) extraction using NE-related labels of words repeatedly collected from unlabeled data. NE-related labels of words are candidate NE classes of each word, NE classes of co-occurring words of each word, and so on. To collect NE-related labels of words, we extract NEs from unlabeled data with an NE extractor. Then we collect NE-related labels of words from the extraction results. We create a new NE extractor using the NE-related labels of each word as new features. The new NE extractor is used to collect new NE-related labels of words. The experimental results using IREX data set for Japanese NE extraction show that our method contributes improved accuracy.
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Iwakura, T. (2010). A Named Entity Extraction using Word Information Repeatedly Collected from Unlabeled Data. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2010. Lecture Notes in Computer Science, vol 6008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12116-6_18
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DOI: https://doi.org/10.1007/978-3-642-12116-6_18
Publisher Name: Springer, Berlin, Heidelberg
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