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：我们基于两种著名的自然语言处理资源——文本语料库和知识库，提出了一个计算驱动的词语相似度数据集。该数据集旨在填补心理语言学研究中的空白，通过在一个由词汇处理中起关键作用的变量所控制的名词对集合中，提供多种语义相似度的量化指标。数据集创建包括三个步骤：1) 计算每个名词的四个关键心理语言特征——具体性、频率、语义和语音邻域密度；2) 基于这四个变量对名词进行配对；3) 为每个名词对分配三种类型的词语相似度度量（基于文本、WordNet和混合嵌入计算得出）。本数据集包含巴斯克语和欧洲西班牙语的名词对信息，未来工作计划将其扩展至更多语言。