Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be discovered and handled. We present TEQUILA, an enabler method for temporal QA that can run on top of any KB-QA engine. TEQUILA has four stages. It detects if a question has temporal intent. It decomposes and rewrites the question into non-temporal sub-questions and temporal constraints. Answers to sub-questions are then retrieved from the underlying KB-QA engine. Finally, TEQUILA uses constraint reasoning on temporal intervals to compute final answers to the full question. Comparisons against state-of-the-art baselines show the viability of our method.

TEQUILA 是一个用于时间问答的方法，它可以在任何基于知识库的问答引擎之上运行。它通过四个阶段来检测问题是否有时间意图，将问题分解和重写成非时间子问题和时间限制，从潜在的基于知识库的问答引擎中检索出非时间子问题的答案，最终使用时间区间上的约束推理来计算整个问题的最终答案，与最先进的基准线相比，显示了我们方法的可行性。

基于知识库的时间问答系统TEQUILA