Method for learning local syntactic relationships for use in example-based information-extraction-pattern learning
First Claim
1. In a computerized example-based pattern learning element of an information-extraction system, said element having as input, texts containing user-identified events and as output, information-extraction patterns that can be used to extract similar events from similar texts, a method for learning local syntactic relationships to be used as components within information-extraction patterns learned by said pattern learning element, said method comprising the steps of:
- analyzing an example text and event given to the learning element to establish that the learning element contains an incomplete current dictionary of local syntactic relationships needed to form paths of relationships between all constituents of the text that participate in the event, thus making the learning element unable to form a new extraction pattern from said example text and event;
thereupon finding the closest pair of constituents within the example text that cannot be related by local syntactic relationships in the current dictionary;
inferring a new local syntactic relationship between said closest pair, said new local syntactic relationship being expressed as a finite state machine;
adding said finite state machine to said dictionary so that said finite state machine can be embedded in patterns produced by said learning element; and
re-invoking the learning element on said example text and said example event to learn an information extraction pattern from said example text and said example event by making use of the newly-inferred local syntactic relationship finite state machine.
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Abstract
A method is provided for learning local syntactic relationships for use in an example-based information-extraction-pattern learning element of an automated information extraction system. The example-based learning element learns information extraction patterns from user-provided examples of texts paired with events the texts contain; these patterns can then be used by the information extraction system to recognize similar events in subsequent texts. The learning element learns patterns by analyzing each example text/event pair to determine paths of local syntactic relationships between constituents in the text that indicate the event. The learning element employs an incomplete dictionary of local syntactic relationships for this analysis. The present invention learns new local syntactic relationships for text/event pairs that cannot be analyzed using the learning element'"'"'s initial, incomplete dictionary of relationships. These new relationships are added to the dictionary, and allow the learning element to learn patterns from example text/event pairs that cannot be analyzed using only the initial dictionary.
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Citations
4 Claims
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1. In a computerized example-based pattern learning element of an information-extraction system, said element having as input, texts containing user-identified events and as output, information-extraction patterns that can be used to extract similar events from similar texts, a method for learning local syntactic relationships to be used as components within information-extraction patterns learned by said pattern learning element, said method comprising the steps of:
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analyzing an example text and event given to the learning element to establish that the learning element contains an incomplete current dictionary of local syntactic relationships needed to form paths of relationships between all constituents of the text that participate in the event, thus making the learning element unable to form a new extraction pattern from said example text and event; thereupon finding the closest pair of constituents within the example text that cannot be related by local syntactic relationships in the current dictionary; inferring a new local syntactic relationship between said closest pair, said new local syntactic relationship being expressed as a finite state machine; adding said finite state machine to said dictionary so that said finite state machine can be embedded in patterns produced by said learning element; and re-invoking the learning element on said example text and said example event to learn an information extraction pattern from said example text and said example event by making use of the newly-inferred local syntactic relationship finite state machine. - View Dependent Claims (2, 3, 4)
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Specification