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Estimating Grammeme Redundancy by Measuring Their Importance for Syntactic Parser Performance

机译:通过测量语法语法分析器性能的重要性来估计语法冗余

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Redundancy is an important psycholinguistic concept which is often used for explanations of language change, but is notoriously difficult to operationalize and measure. Assuming that the reconstruction of a syntactic structure by a parser can be used as a rough model of the understanding of a sentence by a human hearer, I propose a method for estimating redundancy. The key idea is to compare performances of a parser on a given treebank before and after artificially removing all information about a certain grammeme from the morphological annotation. The change in performance can be used as an estimate for the redundancy of the grammeme. I perform an experiment, applying MaltParser to an Old Church Slavonic treebank to estimate grammeme redundancy in Proto-Slavic. The results show that those Old Church Slavonic grammemes within the case, number and tense categories that were estimated as most redundant are those that disappeared in modern Russian. Moreover, redundancy estimates serve as a good predictor of case grammeme frequencies in modem Russian. The small sizes of the samples do not allow to make definitive conclusions for number and tense.
机译:冗余是一种重要的心理语言学概念,通常用于解释语言变化,但众所周知难以操作和测量。假设可以将解析器对句法结构的重构用作人类听众对句子理解的粗略模型,我提出了一种估计冗余的方法。关键思想是在从形态注释中人为地删除有关某个字素的所有信息之前和之后,比较给定树库上解析器的性能。性能的变化可以用作对语素冗余的估计。我进行了一个实验,将MaltParser应用于旧教会的斯拉夫语树库中,以估计原始斯拉夫语中的语素冗余。结果表明,在案例,数量和时态类别中被认为是最多余的那些旧教会斯拉夫语语法,是现代俄语中消失的那些语法。此外,冗余估计值可以很好地预测现代俄语中的格状音素频率。样本数量太小,无法就数量和时态得出明确的结论。

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