Advances in the Automatic Lemmatization of Old English: Class IV Strong Verbs (L-Y)

Roberto Torre
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Abstract

The morphological features of an inflectional language like Old English (OE), which also presents generalized spelling inconsistencies, limit the use of lemmatizing and tagging tools that can be applied to natural languages. Consequently, the development of Natural Language Processing (NLP) models, which crucially depend on lemmatized corpora, is slowed down. Against this background, this article develops a lemmatizer within the framework of Morphological Generation that allows for the type-based automatic lemmatization of OE class IV strong verbs (L–Y). The lemmatizer incorporates a set of algorithms to account for features of inflectional, derivational, morphophonological and diatopic variation. The generated forms are automatically compared with Taylor et al. (2003) and Healey et al. (2004) to confirm their attestation and are assigned a lemma. Overall, the research proves successful in setting up form-lemma associations, while highlighting areas of ambiguity and mismatches. The main conclusion of the article is that taking the route of automatic lemmatization with this methodological framework will contribute to the field of OE lexicography by both lemmatizing attested inflectional forms and by identifying areas for manual revision.
古英语自动词法化的进展:第四类强动词 (L-Y)
像古英语(OE)这样的词形变化语言也存在拼写普遍不一致的问题,其词形特征限制了可用于自然语言的词法化和标记工具的使用。因此,自然语言处理(NLP)模型的开发速度减慢,而这些模型在很大程度上依赖于词法化的语料库。在此背景下,本文在词法生成框架内开发了一种词法生成器,可对 OE 第四类强动词(L-Y)进行基于类型的自动词法生成。该词法生成器采用了一套算法,以考虑到词形变化、派生词、形态音变和异位词的特点。生成的词形会自动与 Taylor 等人(2003 年)和 Healey 等人(2004 年)的词形进行比较,以确认其证明,并分配一个词目。总之,这项研究成功地建立了词形与词素之间的关联,同时突出了模糊和不匹配的地方。文章的主要结论是,采用这种方法框架进行自动词法化,既能将已证实的转折形式词法化,又能找出需要人工修订的地方,从而为外来语词典学领域做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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