The value of learning linguistic structures in relation extraction
نویسندگان
چکیده
The extraction of instances of relations that are conceptually known is an important sub-task of automatic ontology population. We consider an approach that uses a local alignment kernel to learn to recognize linguistic dependency paths of these relations. This approach uses WordNet as a similarity function between concepts. We evaluate its performance by comparing it with a probabilistic approach, based on the co-occurrence of the related entities. Our results show that good results are possible, especially when only a small portion of the data is available.
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