We present a computationally-grounded word similarity dataset based on two well-known Natural Language Processing resources; text corpora and knowledge bases. This dataset aims to fulfil a gap in psycholinguistic research by providing a variety of quantifications of semantic similarity in an extensive set of noun pairs controlled by variables that play a significant role in lexical processing. The dataset creation has consisted in three steps, 1) computing four key psycholinguistic features for each noun; concreteness, frequency, semantic and phonological neighbourhood density; 2) pairing nouns across these four variables; 3) for each noun pair, assigning three types of word similarity measurements, computed out of text, Wordnet and hybrid embeddings. The present dataset includes noun pairs' information in Basque and European Spanish, but further work intends to extend it to more languages.
翻译:我们提供了一个计算机支持的单词相似性数据集,它基于两个著名的自然语言处理资源:文本语料库和知识库。该数据集旨在填补心理语言学研究中的一个空白,通过在一组广泛的名词对中提供多种语义相似度的量化,这些名词对受到对词汇加工起重要作用的变量的控制。数据集的创建包括三个步骤,1)计算每个名词的四个关键心理语言学特征;具体性、频率、语义和音词邻居密度;2)通过这四个变量对名词进行配对;3)针对每个名词对,分配三种类型的单词相似度测量,它们是基于文本、Wordnet 和混合嵌入计算的。本数据集包括巴斯克语和欧洲西班牙语的名词对信息,但未来的工作意图将其扩展到更多的语言。