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- W2100986601 abstract "We used the memory-based learner Timbl (Daelemans et al., 2002) to find names in English and German newspaper text. A first system used only the training data, and a number of gazetteers. The results show that gazetteers are not beneficial in the English case, while they are for the German data. Type-token generalization was applied, but also reduced performance. The second system used gazetteers derived from the unannotated corpus, as well as the ratio of capitalized versus uncapitalized use of each word. These strategies gave an increase in performance." @default.
- W2100986601 created "2016-06-24" @default.
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- W2100986601 date "2003-01-01" @default.
- W2100986601 modified "2023-10-06" @default.
- W2100986601 title "Memory-based named entity recognition using unannotated data" @default.
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- W2100986601 doi "https://doi.org/10.3115/1119176.1119211" @default.
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