Recent advances in Natural Language Processing (NLP) continue to open up new lines of enquiry for lexicography, especially for research areas concerned with semantic categorisation. The aims of this paper fall into two parts. In the first half, the NLP tool Word2Vec is introduced and discussed with respect to unsupervised category formation for Koine Greek, using kinship terms as a demonstration of the model’s utility. The latter half of the paper employs a prototype theory framework to analyse the model’s distributional information in the construction of new dictionary entries for each kinship term. Such NLP-based research highlights the importance of encyclopaedic information for the construction of lexical entries; it also significantly improves upon earlier attempts at categorisation for Koine Greek (Louw and Nida 1988), which fall victim to using the L1 categories of the lexicographer in the construction of semantic domains for the ancient language.

中文翻译：

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我们如何在没有我们自己的影响的情况下研究古希腊类别？使用 word2vec 探索亲属关系术语

自然语言处理 (NLP) 的最新进展继续为词典编纂开辟新的研究方向，尤其是与语义分类相关的研究领域。本文的目的分为两个部分。前半部分介绍并讨论了 NLP 工具 Word2Vec 用于 Koine Greek 的无监督类别形成，使用亲属关系作为模型效用的演示。论文后半部分采用原型理论框架分析模型在为每个亲属词构建新词典条目时的分布信息。这种基于 NLP 的研究强调了百科全书信息对于构建词汇条目的重要性；它还显着改进了早期对 Koine Greek 进行分类的尝试（Louw 和 Nida 1988），