EAGER: Corpus-Based Narrative Semantics

探索性研究早期概念补助金（EAGER）探索叙事的计算分析方法。 尽管叙事的本质无处不在，但自20世纪70年代以来，计算语言学家一直回避对叙事的研究，认为分析故事和文学太困难了。 这个EAGER项目的目标是表明，叙事分析现在是可能的，它的研究也可以相关的实用，基于网络的系统的发展。 该项目的特点是发展一个声明性的，象征性的叙事表示，手动分析的内容单元的叙事使用这种表示的方法，以及自动处理的语料库的叙事，以获得结构和内容为导向的模式的计算方法。例如，可以开发学习模型来识别和描述角色面临的困境，或者识别故事之间的主题相似性。 在该项目的前12个月，研究人员专注于注释方法的开发，一个用于注释短寓言和寓言的收集项目，以及学习算法的开发。 在接下来的六个月里，研究人员计划将这项工作应用到更大的领域，以显示更大的影响-即处理新闻文本的任务，如摘要。 该项目的特点是计算机科学家和文学理论专家之间的合作，以纳入从叙事学角度出发的分析模式。 研究人员将为叙事学和计算语言学社区的进一步工作提供一系列资源，包括注释语料库和注释方法（称为DramaBank）以及注释和自动分析软件;这些将使两个社区能够继续对文学和其他形式的叙事进行新的研究。

This Early-concept Grant for Exploratory Research (EAGER) explores approaches for computational analysis of narrative. Despite the ubiquitous nature of narrative, computational linguists have shied away from research on narrative since the 1970's, viewing analysis of stories and literature as too difficult. The goal of this EAGER project is to show that analysis of narrative is now possible and that its study can also be relevant to the development of practical, web-based systems. The project features the development of a declarative, symbolic representation of narrative, a method for manually analyzing the content units of narrative using this representation, and a computational approach for automatically processing a corpus of narratives to derive structural and content-oriented patterns. For example, a learning model may be developed to identify and describe dilemmas that a character faces or to identify thematic similarity between stories. In the first 12 months of the project, researchers are focusing on the development of the annotation methodology, a collection project for annotations of short fables and parables, and the development of learning algorithms. In the following six months, the researchers plan to apply the work to a larger domain in order to show larger impact -- namely, the processing of news text for tasks such as summarization. The project features a collaboration between computer scientists and an expert in literary theory in order to incorporate modes of analysis that are well-grounded from the perspective of narratology. The researchers will provide a range of resources for further work in the narratology and computational linguistics communities, including the annotated corpus and annotation methodology (called DramaBank) as well as software for annotation and automatic analysis; these will enable both communities to continue a new line of research on literature and other forms of narrative occurring on the web.