Diversity in use of Question and Answering (Q/A) is evolving as a popular application in the area of Natural Language Processing (NLP). The alive unsupervised word embedding approaches are efficient to collect Latent-Semantic data on number of tasks. But certain methods are still unable to tackle issues such as polysemous-unaware with task-unaware phenomena in NLP tasks. https://www.wholelatteslovers.shop/product-category/distribution-tool/