According to an aspect, a pair of related entities that includes a first entity and a second entity is received. Distributional relations are detected between the first entity and the second entity. The detecting includes identifying two sets of entities in a corpus, the first set including the first entity and at least one other entity that is semantically similar to the first entity, and the second set including the second entity and at least one other entity that is semantically similar to the second entity. Semantic relations are detected between entities in the first set and entities in the second set. A relation classifier is trained using the pair of related entities and detected semantic relations. The relation classifier model is applied to a new pair of entities to determine a likelihood of a semantic relation between the entities in the new pair of entities.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-12. (canceled) 13. A computer program product comprising: a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit to perform a method comprising: receiving a pair of related entities that includes a first entity and a second entity; detecting distributional relations between the first entity and the second entity, the detecting including: identifying two sets of entities in a corpus, the first set including the first entity and at least one other entity that is semantically similar to the first entity, and the second set including the second entity and at least one other entity that is semantically similar to the second entity; and detecting semantic relations between entities in the first set and entities in the second set; training a relation classifier model using the pair of related entities and the detected semantic relations; and applying the relation classifier model to a new pair of entities to determine a likelihood of a semantic relation between the entities in the new pair of entities. 14. The computer program product of claim 13, wherein the first entity is located in a first subset of documents in the corpus and the second entity is located in a second subset of the documents in the corpus, the second subset mutually exclusive of the first subset. 15. The computer program product of claim 13, wherein the first entity is located in a first subset of sentences in the corpus and the second entity is located in a second subset of the sentences in the corpus, the second subset mutually exclusive of the first subset. 16. The computer program product of claim 13, wherein the training a relation classifier model includes supervised training. 17. The computer program product of claim 13, wherein the identified semantic relations are used as features to train the relation classifier model. 18. The computer program product of claim 13, wherein the identifying is based on distributional semantics. 19. A system comprising: a memory having computer readable computer instructions; and a processor for executing the computer readable instructions, the computer readable instructions including: receiving a pair of related entities that includes a first entity and a second entity; detecting distributional relations between the first entity and the second entity, the detecting including: identifying two sets of entities in a corpus, the first set including the first entity and at least one other entity that is semantically similar to the first entity, and the second set including the second entity and at least one other entity that is semantically similar to the second entity; and detecting semantic relations between entities in the first set and entities in the second set; training a relation classifier model using the pair of related entities and the detected semantic relations; and applying the relation classifier model to a new pair of entities to determine a likelihood of a semantic relation between the entities in the new pair of entities. 20. The system of claim 19, wherein the first entity is located in a first subset of documents in the corpus and the second entity is located in a second subset of the documents in the corpus, the second subset mutually exclusive of the first subset.