Abstract
Information Extraction (IE) systems today are commonly based on pattern matching. The patterns are regular expressions stored in a customizable knowledge base. Adapting an IE system to a new subject domain entails the construction of a new pattern base --- a time-consuming and expensive task. We describe a strategy for building patterns from examples. To adapt the IE system to a new domain quickly, the user chooses a set of examples in a training text, and for each example gives the logical form entries which the example induces. The system transforms these examples into patterns and then applies meta-rules to generalize these patterns.
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