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Improved Neural Relation Detection for Knowledge Base Question Answering

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Academic year: 2020

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Figure

Figure 1: KBQA examples and its three key components. (a) A single relation example. We first identify the topic entity withentity linking and then detect the relation asked by the question with relation detection (from all relations connecting the topicent
Table 1: An example of KB relation (episodes written) with two types of relation tokens (relation namesand words), and two questions asking this relation
Figure 2: The proposed Hierarchical Residual BiLSTM (HR-BiLSTM) model for relation detection.Note that without the dotted arrows of shortcut connections between two layers, the model will onlycompute the similarity between the second-layer of questions representations and the relation, thus is notdoing hierarchical matching.
Table 2: Accuracy on the SimpleQuestions and WebQSP relation detection tasks (test sets)
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