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On the Semantic Relations and Functional Properties of Noun-Noun Compounds in Mandarin

机译:汉语中名词名词复合词的语义关系和功能性质

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The goal of this research was to determine the distribution of compounds in Mandarin Chinese from the aspect of semantics. In particular, the focus was on two types of compounds: compounds interpreted by semantic relations or by functional properties between constituents. We collected 880 compounds from a dictionary and categorized them into two types of noun-noun compounds in Mandarin, including relation-based compounds (e.g., 中國菜 zhongguocai "Chinese food") and functional property-based compounds (e.g.,柳葉眉 liuyemei "arched eyebrows"). Finally, the frequency of occurrence of the two types of compounds was determined. The results showed that relation-based compounds occurred much more frequently than property-based compounds in our data (96.1% vs. 3.8%). In addition, it was found that within the relation-based compounds, noun-noun compounds using the FOR relation (e.g.,信紙xinzhi "letter paper") had the highest rates of occurrence (37.6%), while the CAUSE relation (e.g.,刀傷daoshang "wounds by a knife") had the lowest rates of occurrence (0.7%). On the other hand, the functional property-based compounds, almost always referring to objects in the NATURAL KIND domain, take metaphorical meanings from individual constituents. Our study suggests that the relation-based meanings for interpreting compounds are common in daily conversation, which could be the dominant strategy people use to interpret novel compounds. This research has practical implications for natural language processing in dealing with segmentation of compounds and multiword expressions in Mandarin and even recognition of novel word combinations.
机译:这项研究的目的是从语义方面确定汉语普通话中化合物的分布。特别地,重点是两种类型的化合物:通过语义关系或成分之间的功能特性来解释的化合物。我们从词典中收集了880种化合物,并将它们分为普通话中的两种名词-名词化合物,包括基于关系的化合物(例如,中国菜中果菜“中国食品”)和基于功能特性的化合物(例如,柳叶眉liuyemei”眉毛拱形”)。最后,确定了两种化合物的出现频率。结果表明,在我们的数据中,基于关系的化合物比基于属性的化合物发生的频率更高(96.1%对3.8%)。此外,还发现在基于关系的复合物中,使用FOR关系的名词-名词复合物(例如,信纸xinzhi“ letter paper”)的发生率最高(37.6%),而在CAUSE关系中(例如,刀伤刀伤“刀伤”的发生率最低(0.7%)。另一方面,基于功能特性的化合物几乎总是引用NATURAL KIND域中的对象,它们从单个成分中获得隐喻含义。我们的研究表明,在日常对话中,基于关系的解释化合物的含义很常见,这可能是人们用来解释新型化合物的主要策略。这项研究对自然语言处理处理普通话中的复合词和多词表达甚至识别新词组合具有实际意义。

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