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Unitizing Plot to Advance Analysis of Narrative Structure (PLANS)

Unitizing Plot to Advance Analysis of Narrative Structure (PLANS)
整合情节以推进叙事结构分析(计划)
批准号:
434552206
负责人:
Professor Dr. Christian Biemann
金额:
$0.0万
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:

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中文摘要
翻译
拟议的项目“统一情节以推进叙事结构分析”(PLANS)是一项跨学科的努力,旨在通过结合理论视角和以实施为重点的方法,探索和建模叙事理论中的情节概念。作为这些考虑的起点,需要注意的是,叙事理论缺乏一个全面的情节理论模型,正如在当前的自然语言处理技术水平下,全面的情节计算建模是不可行的。因此,我们试图通过在中间水平上工作来推进叙事结构的分析:情节单元的建模。对于情节单元,我们处理事件和情节之间的中间层次,或整体叙事结构。因此,情节单元使我们在叙事分析、叙事理论以及自然语言处理方面取得了实质性进展。在PLANS中,我们将以之前event项目中的事件提取为基础,并对其进行调整,以推进情节分析。为此,我们需要考虑到情节是由其文本表示和虚构世界的属性(如人物和事件)决定的。因此,通过对情节单元的建模,我们力求在概念上将话语的文本层面与情节、行动以及总体上的历史层面联系起来;简单地说,我们把叙述的方式和叙述的内容联系起来。通过这种方法,我们努力克服当前在自然语言处理和叙事理论方面的局限性。在自然语言处理中,已经采用了多种方法来提取和理解情节,然而,现有的方法通常不适用于大范围的文本。以叙事理论为指导的方法可以使我们创建更广泛适用的情节计算模型,而基于统一的方法可以更直接地将文本的表面与情节结构联系起来。此外,基于情节单元的分割方法使我们能够从分析较小的、已定义的文本部分发展到分析整个叙事。这简化了计算处理,使使用其他不切实际的处理技术(例如,用于共参考分辨率或语义世界知识建模)成为可能。在叙事理论方面,关注事件和情节之间的中间层次,可以对叙事构成进行更一般的操作化,即解释事件如何组合并转化为叙事文本的原则。这在叙事理论中仍然是一种渴望。此外,我们期望深入了解情节和叙事构成的理论模型之间尚未理论化的概念联系。
英文摘要
The proposed project “Unitizing Plot to Advance Analysis of Narrative Structure” (PLANS) is an interdisciplinary effort towards exploring and modeling concepts of plot in narrative theory by combining a theoretical perspective with an implementation-focused approach. As the starting point to these considerations, it is important to note that narrative theory lacks a comprehensive theoretical model of plot, just as comprehensive computational modeling of plot is infeasible with the current state of natural language processing techniques. Therefore, we seek to advance the analysis of narrative structure by working on an intermediate level: the modeling of plot units. With plot units we tackle the intermediate level between events and plot, or overall narrative structure. Thus plot units enable us to make substantial progress in the analysis of narratives, in narrative theory as well as in natural language processing.In PLANS, we will build on the event extraction in the predecessor EvENT project and adapt it in order to advance plot analysis. For this, we need to take into consideration that plot is determined both by its textual representation and properties of the fictional world, such as characters and events.Therefore, with the modeling of plot units, we strive to also conceptually connect the textual level of discours to plot, action, and generally the level of histoire; in simpler terms: we connect the how of narration with the what of narration.With this approach we strive to overcome current limitations in natural language processing and narrative theory. In natural language processing a variety of approaches to the extraction and understanding of plots have been taken, existing approaches, however, are not generally applicable to wide ranges of texts. An approach guided by narrative theory may enable us to create computational models of plot that are more broadly applicable, with the unitization-based approach enabling a more direct connection from the text’s surface from to its plot structure. Moreover, the segmentation based approach to plot units allows us to progress from the analysis of smaller, defined portions of texts to the entire narrative. This simplifies computational processing, enabling the use of otherwise impractical processing techniques (e.g., for coreference resolution or modeling of semantic world knowledge).With regard to narrative theory, the focus on the intermediate level between events and plot allows for a more general operationalization of narrative constitution, i.e., the principles that explain how events are combined and transformed into narrative text. This is still a desideratum in narrative theory. Moreover, we expect to gain insights into the as yet under-theorized conceptual connections between theoretical models of plot and narrative constitution.
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Joining graph- and vector-based sense representations for semantic end-user information access (JOIN-T 2)
  • 批准号:
    259256643
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2014
  • 负责人:
    Professor Dr. Christian Biemann
  • 依托单位:
Semantic Methods for Computer-supported Writing Aids
  • 批准号:
    249088706
  • 项目类别:
    Research Grants
  • 资助金额:
    $0.0万
  • 财政年份:
    2014
  • 负责人:
    Professor Dr. Christian Biemann
  • 依托单位:
Answering Comparative Questions with Arguments (ACQuA 2.0)
  • 批准号:
    376430233
  • 项目类别:
    Priority Programmes
  • 资助金额:
    $0.0万
  • 财政年份:
    --
  • 负责人:
    Professor Dr. Christian Biemann
  • 依托单位:
海外基金