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【论文阅读】A Comprehensive Survey on Schema-based Event Extraction with Deep Learning

Qian Li et al. 2021

总结：

  • 分类整理了deep learning事件抽取的进展和方法
  1. Event Extraction terminologies 定义
    1. Entity 实体: The entity is an object or group of objects in a semantic category. Entity mainly includes people, organizations, places, times, things, etc.
    2. Event mentions 事件提及: The phrase or sentences that describe the event contains a trigger and corresponding arguments.
    3. Event type 事件类型: The event type describes the nature of the event and refers to the category to which the event corresponds, usually represented by the type of the event trigger.
    4. Event trigger 事件触发词: Event trigger refers to the core unit in event extraction, a verb or a noun. Trigger identification is a key step in pipeline-based event extraction.
    5. Event argument 事件论元: Event argument is the main attribute of events. It includes entities, nonentity participants, and time, and so on.
    6. Argument role 论元角色: An argument role is a role played by an argument in an event, that is, the relationship representation between the event arguments and the event triggers.
  2. Schema-based event extraction includes four sub-tasks 四个子任务
    1. Event classification 事件分类: Event classification is to determine whether each sentence is an event. Furthermore, if the sentence is an event, we need to determine one or several events types

本文标签： 论文SurveyschemaBasedComprehensive

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