A technique for resolving entities provided in a question includes creating respective entity context vectors (ECVs) for respective entities in an applicable knowledge graph (KG). A question is received from a user. A first entity is identified in the question. The first entity is associated with a matching one of the entities in the KG. An ECV for the matching one of the entities in the KG is modified. An answer to the question is generated based on the modified ECV.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of resolving entities included in a question, comprising: creating, using a data processing system, respective entity context vectors (ECVs) for respective entities in an applicable knowledge graph (KG); receiving, using the data processing system, a question from a user; identifying, using the data processing system, a first entity in the question; associating, using the data processing system, the first entity with a matching one of the entities in the KG; modifying, using the data processing system, an ECV for the matching one of the entities in the KG; and generating, using the data processing system, an answer to the question based on the modified ECV. 2. The method of claim 1, wherein the modifying an ECV for the matching one of the entities in the KG includes: adding a new surface form of the first entity to the ECV. 3. The method of claim 1, further comprising: receiving one or more additional questions from the user that are associated with the first entity; and adding one or more additional new surface forms for the first entity to the ECV. 4. The method of claim 3, wherein the new surface forms are generated due to a change in at least one of a user title, a user status, a user association, a time frame, a user organization, and a user location. 5. The method of claim 1, wherein the received question is in a natural language. 6. The method of claim 1, wherein the ECVs include dependency parses for entities included in the ECVs. 7. The method of claim 6, wherein the ECVs further include bags of words, entity type, and known surface forms for entities included in the ECVs. 8. A computer program product configured to transform questions for a question answering (QA) system, the computer program product comprising: a computer-readable storage device; and computer-readable program code embodied on the computer-readable storage device, wherein the computer-readable program code, when executed by a data processing system, causes the data processing system to: create respective entity context vectors (ECVs) for respective entities in an applicable knowledge graph (KG); receive a question from a user; identify a first entity in the question; associate the first entity with a matching one of the entities in the KG; modify an ECV for the matching one of the entities in the KG; and generate an answer to the question based on the modified ECV. 9. The computer program product of claim 8, wherein the computer-readable program code, when executed by the data processing system, further configures the data processing system to: add a new surface form of the first entity to the ECV. 10. The computer program product of claim 8, wherein the computer-readable program code, when executed by the data processing system, further configures the data processing system to: receive one or more additional questions from the user that are associated with the first entity; and add one or more additional new surface forms for the first entity to the ECV. 11. The computer program product of claim 10, wherein the new surface forms are generated due to a change in at least one of a user title, a user status, a user association, a time frame, a user organization, and a user location. 12. The computer program product of claim 8, wherein the received question is in a natural language. 13. The computer program product of claim 8, wherein the ECVs include dependency parses for entities included in the ECVs. 14. The computer program product of claim 13, wherein the ECVs further include bags of words, entity type, and known surface forms for entities included in the ECVs. 15. A data processing system, comprising: a cache memory; and a processor coupled to the cache memory, wherein the processor is configured to: create respective entity context vectors (ECVs) for respective entities in a knowledge graph (KG); receive a question from a user; identify a first entity in the question; associate the first entity with a matching one of the entities in the KG; modify an ECV for the matching one of the entities in the KG; and generate an answer to the question based on the modified ECV. 16. The data processing system of claim 15, wherein the computer-readable program code, when executed by the data processing system, further configures the data processing system to: add a new surface form of the first entity to the ECV. 17. The data processing system of claim 15, wherein the computer-readable program code, when executed by the data processing system, further configures the data processing system to: receive one or more additional questions from the user that are associated with the first entity; and add one or more additional new surface forms for the first entity to the ECV. 18. The data processing system of claim 17, wherein the new surface forms are generated due to a change in at least one of a user title, a user status, a user association, a time frame, a user organization, and a user location. 19. The data processing system of claim 15, wherein the received question is in a natural language. 20. The data processing system of claim 15, wherein the ECVs include dependency parses, bags of words, entity type, and known surface forms for entities included in the ECVs.