英语在线时态和时态标识符的开发

J. Blake
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引用次数: 0

摘要

本文描述了时态和方面标识符的开发,这是一个在线工具,旨在通过利用自然语言处理管道将动词组自动分类为12个语法时态之一,从而帮助英语学习者。目前,还没有网站或应用程序可以自动识别上下文中的时态,时态和方面标识符填补了这一空白。学习者可以使用这个工具来了解语法时态是如何在上下文中使用的。自动识别有限的动词组,并根据识别的时态突出显示动词组中的相关单词并着色。最新部署的系统可以识别简单句、复合句和复合句中的时态。当助动词省略或标注者分配了不正确的词性标注时,会出现假阳性结果。时态标识符的用户界面是一个使用Flask框架创建并从Heroku平台部署的web应用程序。该工具可以用于归纳和演绎教学方法,甚至可以检查论文中的时态一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of an online tense and aspect identifier for English
This article describes the development of a tense and aspect identifier, an online tool designed to help learners of English by harnessing a natural language processing pipeline to automatically classify verb groups into one of 12 grammatical tenses. Currently, there is no website or application that can automatically identify tense in context, and the tense and aspect identifier fills that niche. Learners can use the tool to see how grammatical tenses are used in context. Finite verb groups are automatically identified, and the relevant words in the verb group are highlighted and colorized according to the tense identified. The latest deployed system can identify tenses in simple, compound, and complex sentences. False positive results occur when there is ellipsis of auxiliary verbs or when the tagger assigns the incorrect part-of-speech tag. The user interface of the tense identifier is a web app created using the Flask framework and deployed from the Heroku platform. The tool can be used for inductive and deductive teaching approaches, or even to check for tense consistency in a thesis.
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