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首页> 外文会议>International Seminar on Annotating, Extracting and Reasoning about Time and Events; 20050410-15; Dagstuhl Castle(DE) >Effective Use of TimeBank for TimeML Analysis
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Effective Use of TimeBank for TimeML Analysis

机译：有效使用TimeBank进行TimeML分析

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摘要

TimeML is an expressive language for temporal information, but its rich representational properties raise the bar for traditional information extraction methods when applied to the task of text-to-TimeML analysis. We analyse the extent to which TimeBank, the reference corpus for TimeML, supports development of TimeML-compliant analytics. The first release of the corpus exhibits challenging characteristics: small size and some noise. Nonetheless, a particular design of a time anno-tator trained on TimeBank is able to exploit the data in an implementation which deploys a hybrid analytical strategy of mixing aggressive finite-state processing over linguistic annotations with a state-of-the-art machine learning technique capable of leveraging large amounts of unan-notated data. We present our design, in light of encouraging performance results; we also interpret these results in relation to a close analysis of TimeBank's annotation 'profile'. We conclude that even the first release of the corpus is invaluable; we further argue for more infrastructure work needed to create a larger and more robust reference corpus.
机译：TimeML是时间信息的一种表达语言，但当将其应用于文本到TimeML分析任务时，其丰富的表示属性为传统信息提取方法提高了标准。我们分析TimeML的参考语料库TimeBank支持开发符合TimeML的分析的程度。语料库的第一个版本具有挑战性的特征：小尺寸和一些噪音。尽管如此，经过TimeBank培训的时间注释器的特殊设计仍能够在实现中利用数据，该实现部署了一种混合分析策略，将对语言注释的积极有限状态处理与最新的机器学习相结合能够利用大量未注释数据的技术。鉴于令人鼓舞的性能结果，我们展示了我们的设计；我们还将这些结果与对TimeBank注释“配置文件”的仔细分析相关联。我们得出的结论是，即使是语料库的第一个发行版也无价。我们进一步主张创建更大，更强大的参考语料库需要做更多的基础设施工作。

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