The surprising property of word analogies using vector arithmetic has been observed first in natural language models. In trained models such as skip-gram with negative sampling (SGNS), the word analogy "King is to X as Man is to Woman?" is solved by taking the closest vector to "King -Man + Woman" which happens to be the vector for X = "Queen." The success of this is based loosely on the Pennington et al. conjecture, proven in ref , which states that such word analogies are linear iff p(w|a)/p(w|b) ≈ p(w|x)/p(w|y). In simple terms, if words a and b are found in the same ratios as x and y across all words w of a vocabulary, then there must be a linear analogy between, a, b, x, and y. We show in this work that the same observation can be made with graph-embeddings of molecular graphs.