Distant Supervised Relation Extraction
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چکیده
منابع مشابه
Distant Supervised Relation Extraction with Wikipedia and Freebase
In this paper we discuss a new approach to extract relational data from unstructured text without the need of hand labeled data. Socalled distant supervision has the advantage that it scales large amounts of web data and therefore fulfills the requirement of current information extraction tasks. As opposed to supervised machine learning we train generic, relationand domain-independent extractor...
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Broad-coverage relation extraction either requires expensive supervised training data, or suffers from drawbacks inherent to distant supervision. We present an approach for providing partial supervision to a distantly supervised relation extractor using a small number of carefully selected examples. We compare against established active learning criteria and propose a novel criterion to sample ...
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A promising approach to relation extraction, called weak or distant supervision, exploits an existing database of facts as training data, by aligning it to an unlabeled collection of text documents. Using this approach, the task of relation extraction can easily be scaled to hundreds of different relationships. However, distant supervision leads to a challenging multiple instance, multiple labe...
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Supervised machine learning methods have been widely used in relation extraction that finds the relation between two named entities in a sentence. However, their disadvantages are that constructing training data is a cost and time consuming job, and the machine learning system is dependent on the domain of the training data. To overcome these disadvantages, we construct a weakly labeled data se...
متن کاملImproving distant supervision using inference learning
Distant supervision is a widely applied approach to automatic training of relation extraction systems and has the advantage that it can generate large amounts of labelled data with minimal effort. However, this data may contain errors and consequently systems trained using distant supervision tend not to perform as well as those based on manually labelled data. This work proposes a novel method...
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