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Named entity learning and verification: EM in large corpora

The regularity of named entities is used to learn names and extract named entities. Having only a few name elements and a set of patterns the algorithm learns new names and its elements. A verification step assures quality using a large background corpus. Further improvement is reached through classifying the newly learnt elements on character level. Moreover, unsupervised rule learning is discussed.