Concrete words (e.g., apple) are often described in the literature to share more semantic features across languages than abstract words (e.g., appetite). We test this hypothesis using multilingual aligned word embeddings by measuring the distance between words and their nearest neighbor in other languages, and examining whether shorter distances predicted higher concreteness ratings in six languages: Dutch, English, French, Cypriot Greek, Mandarin, and Portuguese. The relationship between concreteness and cross-linguistic distance varied across languages, suggesting that concreteness does not uniformly correspond to cross-linguistic semantic relatedness. Our attempt highlights the potential of using aligned word embeddings for operationalizing psycholinguistic constructs.

The literature on adjective ordering abounds with proposals meant to account for why certain adjectives appear before others in multi-adjective strings (e.g., the small brown box). However, these proposals have been developed and tested primarily in isolation and based on English; few researchers have looked at the combined performance of multiple factors in the determination of adjective order, and few have evaluated predictors across multiple languages. The current work approaches both of these objectives by using technologies and datasets from natural language processing to look at the combined performance of existing proposals across 32 languages. Comparing this performance with both random and idealized baselines, we show that the literature on adjective ordering has made significant meaningful progress across its many decades, but there remains quite a gap yet to be explained.