Semi-supervised Relation Extraction using EM Algorithm
نویسندگان
چکیده
Relation Extraction is the task of identifying relation between entities in a natural language sentence. We propose a semisupervised approach for relation extraction based on EM algorithm, which uses few relation labeled seed examples and a large number of unlabeled examples (but labeled with entities). We present analysis of how unlabeled data helps in improving the overall accuracy compared to the baseline system using only labeled data. This work therefore shows the efficacy of a sound theoretical framework exploiting an easily obtainable resource named “unlabeled data” for the problem of relation extraction.
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