First generation knowledge maps used the techniques described in the previous paper, but did not define how conditional facts should be handled in the fact extraction and knowledge mapping process. To describe this issue, a slight digression is necessary. These statements are adorned with various sorts of punctuation so that they can be scoped and parsed, then compiled or interpreted and then executed by the machine. In knowledge mapping, we extract facts from the literature that represent cause and effect relationships. Facts that share common entities can be drawn into knowledge maps.
Relationships appear in English as verb and prepositional phrases.
Entities, objects, substances and things appear as noun phrases. Nouns should not appear in verb phrases, and vica versa, though because of the frailties of English, nouning a verb and verbing a noun often happen and must be dealt with. When translating English journal text into sets of cause and effect relationships, facts sometimes appear that do not properly fit into the framework of aRb because they are dependent on some condition that is external to aRb . In other words they are conditional facts, that is, facts that are only facts if some other condition is satisfied. Consider the following text, in a paper on proteins in growth and signaling pathways important to understanding cancer.