A system includes a knowledge canvassing system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide a training system for generating benchmark data for the knowledge canvassing system. The training system is configured to resolve a first entity to an entry in a knowledge base of reference documents, identify a second entity included in the entry, and assign a weight to the second entity based on a location of the second entity in the entry or a number of mentions of the second entity in the entry.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for generating benchmark data for a knowledge canvassing system, comprising: resolving, by a training system executing on a computer, a first entity to an entry in a knowledge base of reference documents; identifying, by the training system, a plurality of entities included in the entry; and assigning, by the training system, weights to each of the plurality of entities based on a location of each of the plurality of entities in the entry or a number of mentions of each of the plurality of entities in the entry. 2. The method of claim 1, wherein the resolving a first entity includes matching a title of the entry to the first entity. 3. The method of claim 1, wherein the identifying the plurality of entities includes running an information extraction tool over the entry. 4. The method of claim 1, wherein a second entity included in the plurality of entities is assigned a larger weight than a third entity included in the plurality of entities in response to a determination that the second entity is located prior to the third entity in the entry. 5. The method of claim 4, wherein the second entity is assigned a weight equal to 1 n , where n is a paragraph number in the entry where the second entity first occurs. 6. The method of claim 1, wherein a second entity included in the plurality of entities is assigned a larger weight than a third entity included in the plurality of entities in response to a determination that the second entity occurs more often than the third entity in the entry. 7. The method of claim 1, wherein a second entity included in the plurality of entities is assigned an initial weight of 0 and for each paragraph the second entity occurs in the entry an incremental weight equal to 1 n is added to the initial weight to generate a total weight for the second entity, where n is a paragraph number where the second entity occurs in the entry. 8. A system, comprising: a knowledge canvassing system executed by a computer; a processor; and a memory coupled to the processor, the memory encoded with instructions that when executed cause the processor to provide a training system for generating benchmark data for the knowledge canvassing system, the training system configured to: resolve a first entity to an entry in a knowledge base of reference documents; identify a second entity included in the entry; and assign a weight to the second entity based on a location of the second entity in the entry or a number of mentions of the second entity in the entry. 9. The system of claim 8, wherein the training system is configured to resolve the first entity by matching a title of the entry to the first entity. 10. The system of claim 8, wherein the training system is configured to identify the second entity by running an information extraction tool over the entry. 11. The system of claim 8, wherein the training system is further configured to identify a third entity included in the entry and assign the weight of the second entity a larger value than a weight of the third entity in response to a determination that the second entity is located prior to the third entity in the entry. 12. The system of claim 8, wherein the weight of the second entity is equal 1 n , where n is a paragraph number in the entry where the second entity first occurs. 13. The system of claim 8, wherein the training system is further configured to identify a third entity included in the entry and assign the weight of the second entity a larger value than a weight of the third entity in response to a determination that the second entity occurs more often than the third entity. 14. The system of claim 8, wherein the training system is configured to assign an initial weight of 0 to the second entity and, for each paragraph the second entity occurs in the entry, an incremental weight equal to 1 n is added to the initial weight to generate a total weight, where n is a paragraph number in the entry where the second entity occurs in the entry. 15. A computer program product for generating benchmark data for a knowledge canvassing system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: resolve a first entity to an entry in a knowledge base of reference documents; identify a second entity included in the entry; and assign a weight to the second entity based on a location of the second entity in the entry or a number of mentions of the second entity in the entry. 16. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to resolve the first entity by matching a title of the entry to the first entity. 17. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to identify the second entity by running an information extraction tool over the entry. 18. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to identify a third entity included in the entry and assign the weight of the second entity a larger value than a weight of the third entity in response to a determination that the second entity is located prior to the third entity in the entry. 19. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to identify a third entity included in the entry and assign the weight of the second entity a larger value than a weight of the third entity in response to a determination that the second entity occurs more often than the third entity. 20. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to assign an initial weight of 0 to the second entity and, for each paragraph the second entity occurs in the entry, an incremental weight equal to 1 n is added to the initial weight to generate a total weight, where n is a paragraph number in the entry where the second entity occurs in the entry.