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Formal query generation aims to generate correct executable queries forquestion answering over knowledge bases (KBs), given entity and relationlinking results. Current approaches build universal paraphrasing or rankingmodels for the whole questions, which are likely to fail in generating queriesfor complex, long-tail questions. In this paper, we propose SubQG, a new querygeneration approach based on frequent query substructures, which helps rank theexisting (but nonsignificant) query structures or build new query structures.Our experiments on two benchmark datasets show that our approach significantlyoutperforms the existing ones, especially for complex questions. Also, itachieves promising performance with limited training data and noisyentity/relation linking results.

Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering