Improving event prediction by representing script participants

机译：通过代表脚本参与者来改善事件预测

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Automatically learning script knowledge has proved difficult, with previous work not or just barely beating a most-frequent baseline. Script knowledge is a type of world knowledge which can however be useful for various task in NLP and psycholinguistic modelling. We here propose a model that includes participant information (i.e., knowledge about which participants are relevant for a script) and show, on the Dinners from Hell corpus as well as the InScript corpus, that this knowledge helps us to significantly improve prediction performance on the narrative cloze task.

机译：事实证明，自动学习脚本知识很困难，以前的工作没有或仅仅超过了最常见的基准。脚本知识是世界知识的一种，但是对于NLP和心理语言建模中的各种任务可能很有用。我们在这里提出一个包含参与者信息（即，有关哪些参与者与脚本有关的知识）的模型，并在地狱语料集晚宴和InScript语料集上显示该知识有助于我们显着提高对象的预测性能。叙述性完形填空任务。

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《Conference on the North American Chapter of the Association for Computational Linguistics: Human Language Technologies》|2016年|546-551|共6页
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Simon Ahrendt; Vera Demberg;
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4. Improving event prediction by representing script participants [C] . Simon Ahrendt, Vera Demberg Conference on the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 2016

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Improving event prediction by representing script participants

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