Because REALM pre-computes language models based on its corpus and does not require any hand-tagged seeds, it is far more scalable than approaches that learn models for each individual relation from handtagged data.
rEALM is ideally suited for open information extraction where the relations of interest are not specified in advance and their number is potentially vast.