As the processing power of mobile terminals increases, wireless network applications such as voice assistants can put more context-sensitive tasks on the mobile terminals, thus reducing the wireless network bandwidth needed and the cost of data storage in the cloud. Co-reference annotation, identifying the same semantics in context, is one of the critical techniques in these tasks. However, there are some problems with the existing co-reference annotation standards. First, the annotation is incomplete. Second, the types of annotated mentions are inconsistent. Third, there are currently no metrics for the above characteristics. Analyzing the above-mentioned issues, this paper proposes a new co-reference annotation standard. The new standard can annotate more semantics and co-reference relations and only adopts two types of mentions for annotation. Meanwhile, this paper presents a performance evaluation corpus and designs three performance metrics for evaluating the new standard according to the completeness of semantic annotation, the completeness of co-reference annotation, and the consistency of mention. The experiment shows that the new standard outperforms all the baseline methods and achieves 0.95 in the completeness of semantic annotation, 0.68 in the completeness of co-reference annotation, and 0.57 in the consistency of types of mentions.

随着移动终端处理能力的提高，语音助手等无线网络应用可以将更多上下文相关的任务放在移动终端上，从而降低所需的无线网络带宽和云端数据存储成本。共同引用注释，在上下文中识别相同的语义，是这些任务中的关键技术之一。然而，现有的共同参考注释标准存在一些问题。首先，注释不完整。其次，注释提及的类型不一致。第三，目前没有针对上述特征的指标。针对上述问题，本文提出了一种新的共参考标注标准。新标准可以标注更多的语义和共指关系，并且只采用两种类型的mention进行标注。同时，本文提出了一个绩效评价语料库，并根据语义标注的完整性、共指标注的完整性和提及的一致性设计了三个评价新标准的绩效指标。实验表明，新标准优于所有基线方法，语义标注完整性达到 0.95，共指标注完整性达到 0.68，提及类型一致性达到 0.57。