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Free keywords:
Computer Science, Information Retrieval, cs.IR,Computer Science, Computation and Language, cs.CL
Abstract:
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.
