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Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena

机译:走向文学文本的共指:分析领域特定现象

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摘要

Coreference resolution is the task of grouping together references to the same discourse entity. Resolving coreference in literary texts could benefit a number of Digital Humanities (DH) tasks, such as analyzing the depiction of characters and/or their relations. Domain-dependent training data has shown to improve coreference resolution for many domains, e.g. the biomedical domain, as its properties differ significantly from news text or dialogue, on which automatic systems are typically trained. This also holds for literary texts. We therefore analyze the specific properties of coreference-related phenomena on a number of texts and give directions for the adaptation of annotation guidelines. As some of the adaptations have profound impact, we also present a new annotation tool for coreference, with a focus on enabling annotation of long texts with many discourse entities.
机译:共指解析是将同一个话语实体的参考分组在一起的任务。解决文学文本中的共指可能有益于许多数字人文科学(DH)任务,例如分析人物的描绘和/或其关系。依赖域的训练数据已经显示出可以提高许多域的共指解析度,例如生物医学领域,因为其性质与新闻文本或对话(通常在其上训练自动系统)有很大不同。这也适用于文学作品。因此,我们在许多文本上分析了与共指相关的现象的具体性质,并为适应注释准则提供了指导。由于某些改编具有深远的影响,因此,我们还提供了一种用于共指的新注释工具,重点是使具有许多话语实体的长文本注释成为可能。

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