In this work, we take the GloRE approach further and apply it to large-scale, domainindependent data labeled with distant supervision, with the goal of learning general-purpose textual relation embeddings.
we create the largest ever distant supervision dataset by linking the entire English ClueWeb09 corpus (half a billion of web documents) to the latest version of Freebase (Bollacker et al., 2008), which contains 45 million entities and 3 billion relational facts.