Issues with the Unergative/Unaccusative Classification of the Intransitive Verbs

Nitesh Surtani, Khushboo Jha, Soma Paul
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引用次数: 3

Abstract

The paper abandons a strict two-way sub-classification of intransitive verbs into unaccuasative and unergative for Hindi and proposes a distribution plotting of the same in a diffusion chart. The diagnostics tests that Bhatt (2003) applied on Hindi data are ranked for their efficiency of attributing correct sub-class to verbs. The diffusion chart shows that a tripartite classification handles the issue of classification of intransitive verbs in a better manner than the classical binary approach. The tripartite classification is as follows: (1) Verbs that take animate subject and are compatible with adverb of volitionality; (2) Verbs that take animate subject but are not compatible with adverb of volitionality; and (3) Verbs that take inanimate subject. The classification is of immense advantage for various NLP tasks such as machine translation, natural language generation.
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不及物动词的非否定/非宾格分类问题
本文放弃了印度语中不及物动词严格的双向子分类,即非准确动词和非否定动词,并在扩散图中提出了它们的分布图。Bhatt(2003)在印地语数据上应用的诊断测试因其为动词赋予正确子类的效率而排名。扩散图表明,与经典的二元分类方法相比,三元分类方法更好地处理了不及物动词的分类问题。这三方面的分类是:(1)带有动性主语并与意志性副词相容的动词;(2)带有动性主语但与意志性副词不相容的动词;(3)主语为无生命主语的动词。该分类对于机器翻译、自然语言生成等各种NLP任务具有巨大的优势。
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