This dataset contains the subs2vec embeddings for English, as presented in https://zenodo.org/records/17243814. The embeddings were trained on large-scale subtitle corpora and represent semantic vector spaces derived from naturalistic language use in films and television from the OpenSubtitles 2018 datasets: https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles. For this language, we provide all embedding variants explored in the study. Specifically, the dataset includes vectors generated under different combinations of: Dimensionality: multiple vector sizes (e.g., 100, 200, 300, …) Window size: varying context windows (e.g., 2, 5, 10, …) Each file corresponds to a unique configuration (dimension × window size). Each file contains the vocabulary for that language (column 1) and then the embedding values (columns 2 through dimension size + 1). If you use this dataset, please cite: Manuscript: https://doi.org/10.5281/zenodo.17243812 Data: This Zenodo dataset (using the DOI provided here) sha256sums: en_500_3_cbow_wxd.csv.bz2 19485a54b2249c0897da166814c90437ce4f49ef56e7b54c8ed1444161f29e3b en_500_3_sg_wxd.csv.bz2 c298bc9468a71ec3c6e99f3cafe670cce91fe3e85d968fa5a9cc44769d7c5795 en_500_4_cbow_wxd.csv.bz2 ab46058fa7339f3305ee68b9fa10be2fb0469318d89fdb2e819c60d1681dcfd1