| Abstract | Our experiments use Freebase, a large semantic database of several thousand relations, to provide distant supervision . |
| Architecture | The intuition of our distant supervision approach is to use Freebase to give us a training set of relations and entity pairs that participate in those relations. |
| Architecture | The distant supervision assumption is that if two entities participate in a relation, any sentence that contain those two entities might express that relation. |
| Discussion | Our results show that the distant supervision algorithm is able to extract high-precision patterns for a reasonably large number of relations. |
| Introduction | Distant supervision is an extension of the paradigm used by Snow et al. |
| Introduction | Our algorithm uses Freebase (Bollacker et al., 2008), a large semantic database, to provide distant supervision for relation extraction. |
| Introduction | The intuition of distant supervision is that any sentence that contains a pair of entities that participate in a known Freebase relation is likely to express that relation in some way. |
| Previous work | Perhaps most similar to our distant supervision algorithm is the effective method of Wu and Weld (2007) who extract relations from a Wikipedia page by using supervision from the page’s infobox. |