JUNLG-MSR: A Machine Learning Approach of Main Subject Reference Selection with Rule Based Improvement
نویسندگان
چکیده
The GREC-MSR task is to generate appropriate references to an entity in the context of a piece of discourse longer than a sentence. In MSR ’09 run of this task, the main aim is to select the actual main subject reference (MSR) from a list of given referential expressions that is appropriate in context. We used a machine learning approach augmented with some rules to select the most appropriate referential expression. Our approach uses the training set for learning and then combines some of the rules found by observation to improve the system.
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