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Large, huge or gigantic? Identifying and encoding intensity relations among adjectives in WordNet

机译:大,大还是巨大?在WordNet中识别和编码形容词之间的强度关系

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摘要

We propose a new semantic relation for gradable adjectives in WordNet, which enriches the present, vague, similar relation with information on the degree or intensity with which different adjectives express a shared attribute. Using lexical-semantic patterns, we mine the Web for evidence of the relative strength of adjectives like “large”, “huge” and “gigantic” with respect to their attribute (“size”). The pairwise orderings we derive allow us to construct scales on which the adjectives are located. To represent the intensity relation among gradable adjectives in WordNet, we combine ordered scales with the current WordNet dumbbells based on the relation between a pair of central adjectives and a group of undifferentiated semantically similar adjectives. A new intensity relation links the adjectives in the dumbbells and their concurrent representation on scales. Besides capturing the semantics of gradable adjectives in a way that is both intuitively clear as well as consistent with corpus data, the introduction of an intensity relation would potentially result in several specific benefits for NLP.
机译:我们为WordNet中的可分级形容词提出了一种新的语义关系,该语义关系丰富了当前的,模糊的,相似的关系,并包含了不同形容词表达共享属性的程度或强度的信息。使用词汇语义模式,我们在Web上挖掘了形容词(如“大”,“巨大”和“硕大”)相对于其属性(“大小”)的相对强度的证据。我们得出的成对排序使我们能够构造形容词所在的标度。为了表示WordNet中可分级形容词之间的强度关系,我们基于一对中心形容词与一组未分化的语义相似形容词之间的关系,将有序标度与当前的WordNet哑铃相结合。一个新的强度关系将哑铃中的形容词及其在比例尺上的同时表示联系起来。除了以直观直观的方式并与语料库数据一致的方式捕获可分级形容词的语义外,引入强度关系还可能为NLP带来一些特定的好处。

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