QCSE: A Pretrained Quantum Context-Sensitive Word Embedding for Natural Language Processing

This dataset contains two text corpora: an English corpus and a smaller Fulani corpus (Fulfulde, Adamawa dialect). The corpora are used to construct context–center word pair training samples for the Quantum Context-Sensitive Embedding (QCSE) model. These datasets enable the evaluation of the model’s ability to learn and represent semantic relationships between context words and target (center) words. Using two corpora of different sizes and languages also allows the analysis of QCSE performance under varying data availability conditions.