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：我们提出了一个基于两种著名的自然语言处理资源（文本语料库和知识库）的计算驱动的词语相似性数据集。该数据集旨在填补心理语言学研究中的空白，通过提供受词汇处理中关键变量控制的大量名词对上的多种语义相似性量化指标。数据集的创建包括三个步骤：1）为每个名词计算四个关键心理语言学特征——具体性、频率、语义和音位邻域密度；2）根据这四个变量配对名词；3）为每个名词对分配三种类型的词语相似性度量，分别基于文本、Wordnet和混合嵌入计算。本数据集包含巴斯克语和欧洲西班牙语的名词对信息，但后续工作拟将其扩展至更多语言。