biostudies-literatureShafaei-Bajestan EEuropean Research CouncilEberhard Karls Universität TübingenCompetence Network for Scientific High Performance Computing in Bavaria369-413https://www.ebi.ac.uk/biostudies/studies/S-EPMC11554741biostudies-literatureUnknown34(4)Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similarMorphology (Dordrecht, Netherlands)The pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics.PMC11554741742545Moradipour-Tari MShafaei-Bajestan EBaayen RHUhrig PfalseThe pluralization palette: unveiling semantic clusters in English nominal pluralization through distributional semantics.Using distributional semantics, we show that English nominal pluralization exhibits semantic clusters. For instance, the change in semantic space from singulars to plurals differs depending on whether a word denotes, e.g., a fruit, or an animal. Languages with extensive noun classes such as Swahili and Kiowa distinguish between these kind of words in their morphology. In English, even though not marked morphologically, plural semantics actually also varies by semantic class. A semantically informed method, CosClassAvg, is introduced that is compared to two other methods, one implementing a fixed shift from singular to plural, and one creating plural vectors from singular vectors using a linear mapping (FRACSS). Compared to FRACSS, CosClassAvg predicted plural vectors that were more similar2024-01-01T00:00:00Z20242026-07-11T03:20:38.076Z2025-04-05T18:39:54.908ZS-EPMC115547413954005910.1007/s11525-024-09428-9