To generate Poincaré embeddings from a natural language text corpus, the author converted the text to a list of directed edges in the format $u,v,weight$, where $v$ is a hypernym of $u$, as input to the Poincaré embeddings algorithm, using the method described by Dhingra et al. (2018). They constructed a co-occurrence graph $G = \{(u, v)\}$ that includes all pairs of words that occur within a fixed window of each other. Each edge $(u, v)$ in the graph has a weight $w = f^c$, where $f$ is the frequency of the co-occurrence pairs in the corpus and $c$ is a downsampling constant.