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Determining the significance of an event in the context of a natural language query

机译:在自然语言查询的上下文中确定事件的重要性

摘要

A knowledge graph is built based on a corpus stored in the computer system. The corpus includes a set of events and each event includes a respective set of entities. A first set of entities is identified in the NLQ. The first set of entities is used to identify a first set of significant events in the selected corpus in a first search depth. A second set of entities is identified in the first set of significant events. The knowledge graph determines which ones of the second set of entities are related to the entities in the first set of entities to produce a filtered second set of entities. The filtered second set of entities is used to identify a second set of significant events in the selected corpus in a second search depth. Members of the first and second set of significant events are presented to a user.
机译:基于存储在计算机系统中的语料库构建知识图。语料库包括一组事件,每个事件包括一组相应的实体。在NLQ中标识了第一组实体。第一组实体用于在第一搜索深度中识别所选语料库中的重要事件的第一组。在第一组重要事件中识别出第二组实体。知识图确定第二组实体中的哪些与第一组实体中的实体相关,以产生过滤后的第二组实体。过滤的第二组实体用于在第二搜索深度中识别所选语料库中的第二组重要事件。第一和第二组重要事件的成员被呈现给用户。

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