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Rule-based Coreference Resolution in German Historic Novels

机译:德国历史小说中基于规则的共指解析

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摘要

Coreference resolution (CR) is a key task in the automated analysis of characters in stories. Standard CR systems usually trained on newspaper texts have difficulties with literary texts, even with novels; a comparison with newspaper texts showed that average sentence length is greater in novels and the number of pronouns, as well as the percentage of direct speech is higher. We report promising evaluation results for a rule-based system similar to [Lee et al. 2011], but tailored to the domain which recognizes coreference chains in novels much better than CR systems like CorZu. Rule-based systems performed best on the CoNLL 2011 challenge [Pradhan et al. 2011]. Recent work in machine learning showed similar results as rule-based systems [Durett et al. 2013]. The latter has the advantage that its explanation component facilitates a fine grained error analysis for incremental refinement of the rules.
机译:共指解析(CR)是自动分析故事中人物的关键任务。通常对报纸文本进行培训的标准CR系统在文学文本甚至小说方面都存在困难。与报纸文本的比较表明,小说中平均句子长度更长,代词数量更多,直接讲话的百分比更高。我们报告了类似于[Lee等人的基于规则的系统的有希望的评估结果。 [2011年],但针对的领域是量身定制的,该领域能够识别小说中的共指链,比CorZu等CR系统要好得多。基于规则的系统在CoNLL 2011挑战赛中表现最佳[Pradhan等。 2011]。机器学习的最新工作显示出与基于规则的系统相似的结果[Durett等。 2013]。后者的优势在于其解释组件有助于对规则进行细化的细粒度错误分析。

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  • 会议地点 Denver CO(US)
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    Wuerzburg university, Institute for Computer Science Am Hubland D-97074 Wuerzburg, Germany;

    Wuerzburg university, Institute for Computer Science Am Hubland D-97074 Wuerzburg, Germany;

    Wuerzburg university, Institute for German Studies Am Hubland D-97074 Wuerzburg, Germany;

    Wuerzburg university, Institute for German Studies Am Hubland D-97074 Wuerzburg, Germany;

    Wuerzburg university, Institute for German Studies Am Hubland D-97074 Wuerzburg, Germany;

    Wuerzburg university, Institute for German Studies Am Hubland D-97074 Wuerzburg, Germany;

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