The Unbearable Lightness of Morph Classification

被引：0
作者：
John, Vojtech [1 ]
Zabokrtsky, Zdenek [1 ]
机构：
[1] Charles Univ Prague, Fac Math & Phys, Inst Formal & Appl Linguist, Malostranske Namesti 25, Prague 11800, Czech Republic
来源：
TEXT, SPEECH, AND DIALOGUE, TSD 2023 | 2023年 / 14102卷
关键词：
morphology; morphological analysis; morph classification; DeriNet;
D O I：
10.1007/978-3-031-40498-6_10
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In light of the recent push for the creation and unification of large morphologically annotated resources, there is a call for (preferably language-independent, low-resource) methods of morph classification. This paper reports on a pilot experiment on morph classification of the Czech language. We have performed two experiments - root morph recognition and complete morph classification. By exploiting simple quantitative methods and - in some cases - available Czech morphological resources, we have achieved morph-level precision of respectively 96.7% and 88.3%.
引用
收藏
页码：105 / 115
页数：11
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