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Compound Terms and Their Multi-word Variants: Case of German and Russian Languages

机译:复合术语及其多字变种:德语和俄语的情况

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The terminology of any language and any domain continuously evolves and leads to a constant term renewal. Terms undergo a wide range of morphological and syntactic variations which have to be handled by any NLP applications. If the syntactic variations of multiword terms have been described and tools designed to process them, only a few works studied the syntagmatic variants of compound terms. This paper is dedicated to the identification of such variants, and more precisely to the detection of synonymic pairs that consist of “compound term - multi-word term”. We describe a pipeline for their detection, from compound recognition and splitting to alignment of the variants with original terms, through multi-word term extraction. The experiments are carried out for two compound-producing languages, German and Russian, and two specialised domains: wind energy and breast cancer. We identify variation patterns for these two languages and demonstrate that the transformation of a morphological compound into a syntagmatic compound mainly occurs when the term denomination needs to be enlarged.
机译:任何语言和任何域的术语都不断发展并导致常数续期。术语经历了广泛的形态和句法变异,必须由任何NLP应用程序处理。如果已经描述了多字术语的句法变化和旨在处理它们的工具,则只有少数作品研究了复合术语的Syntmatic变体。本文旨在识别这些变体,更精确地检测由“复合术语 - 多字词”组成的同义对。通过多字词术语提取,我们描述了一种用于其检测的管道,从复合识别和分裂与原始术语的变体对齐。实验是针对两种复合语言,德国和俄罗斯和两个专业领域进行的实验:风能和乳腺癌。我们识别这两种语言的变化模式,并证明了当需要扩大的术语面积时,将形态化合物转化为同种性化合物。

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