We consider the problem of answering natural language questions over a Knowledge Graph, in the case of systems that must evolve over time in a production environment. One of the key issues is that we can expect that the system will receive questions that cannot be answered with the current state of the Knowledge Graph. We discuss here the challenges we need to address in this scenario and the expected behavior of this kind of Lifelong learning system. We also suggest a first task to address this problem and a possible procedure to build a benchmark.
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