For the first problem, we relax the expressedat-least-once assumption, and instead assume that " a relation holding between two entities can be either expressed explicitly or inferred implicitly from all sentences that mention these two entities" (see Figure  1 for a simple illustration).
after automatically extracting features within each sentence using a convolutional architecture, we employ cross-sentence max-pooling to select features across different sentences, and then aggregate the most significant features into a vector representation for each entity pair.