Word2Vec Simulator
See how words become vectors — and why 'king − man + woman ≈ queen'.
Word embeddings turn each word into a point in a high-dimensional space, placing similar meanings close together. This simulator lets you poke at that idea without any setup.
Start by picking a word and looking at its nearest neighbors. Then try the classic analogy — king − man + woman — and see which word lands closest.
Notice how semantic relationships (gender, tense, country–capital) show up as consistent directions in the space.