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A Memory Based Approach to Learning Shallow Natural Language Patterns

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Figure

Figure 1: A candidate subsequence with some of its context, and 5 matching tiles found in the training corpus
Table 2: Distribution of pattern lengths, total num- ber of patterns and average length in the training data
Figure 2: Recall-Precision curves for NP, VO, and SV; 0.1 < 0 < 0.99
Table 3: Results with optimal parameter settings for context size and threshold, and breakeven points

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