English word2vec embeddings trained on OpenSubtitles Part 3

This dataset contains the subs2vec embeddings for [Language Name], 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) sha256-hashes: en_200_3_sg_wxd.csv.bz2 d87de6051c5005ae1c0b2cef9892c43a4186c65e9b936a76b7aef09be3f05d6b en_200_4_cbow_wxd.csv.bz2 d5b4af384791fae7d240977dffcc21f21648849fac4e8e3d70de4d00a398f732 en_200_4_sg_wxd.csv.bz2 7b05d89bc357763b19a8bda5d6f905e02cfd5974c4c3879761635ed2a528ad21 en_200_5_cbow_wxd.csv.bz2 e39f5e3e119e892a2b0ac6c715b72679ece2f1dcacf370ea6de25baf6d4a37ae en_200_5_sg_wxd.csv.bz2 8cf198b75697cbfab10d3614b894e0ae52c220759ffcff0ec4ed320b739dac66 en_200_6_cbow_wxd.csv.bz2 c08e7bb1ddd2faed730f801bc6ed297683ec66404b02109da8eab3019079a1ef en_200_6_sg_wxd.csv.bz2 0fabc3289a5759f0513907400bd05751bcaeab92338ddd66fcc4829b1e6f0172