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Type-aware Convolutional Neural Networks for Slot Filling
2019
The Journal of Artificial Intelligence Research
The slot filling task aims at extracting answers for queries about entities from text, such as "Who founded Apple". In this paper, we focus on the relation classification component of a slot filling system. We propose type-aware convolutional neural networks to benefit from the mutual dependencies between entity and relation classification. In particular, we explore different ways of integrating the named entity types of the relation arguments into a neural network for relation classification,
doi:10.1613/jair.1.11725
fatcat:yjalhe74a5bm3ea7pg5lfwvyre