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 configured to generate benchmark data, each benchmark datum including a set of one or more benchmark input entities and a set of one or more benchmark output entities associated with the one or more benchmark input entities, query the knowledge canvassing system with each set of benchmark input entities, receive, for each set of benchmark input entities queried, an output result from the knowledge canvassing system that includes a set of zero or more knowledge canvassing system output entities, and generate an evaluation score for each set of knowledge canvassing system output entities based on a comparison of the knowledge canvassing system output entities with the set of benchmark output entities.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: generating benchmark data, each benchmark datum including a set of one or more benchmark input entities and a set of one or more benchmark output entities associated with the one or more benchmark input entities; querying, by a training system executing on a computer, a knowledge canvassing system with each set of benchmark input entities; receiving, by the training system, for each set of benchmark input entities queried, an output result from the knowledge canvassing system that includes a set of zero or more knowledge canvassing system output entities; and generating, by the training system, an evaluation score for each set of knowledge canvassing system output entities based on a comparison of the knowledge canvassing system output entities with the set of benchmark output entities. 2. The method of claim 1, wherein the comparison includes matching a first knowledge canvassing system output entity in a first set of knowledge canvassing system output entities to a first benchmark output entity in a first set of benchmark output entities. 3. The method of claim 2, wherein the generating the evaluation score is further based on an estimation of a degree to which an unmatched knowledge canvassing system output entity in the first set of knowledge canvassing system output entities relates to any benchmark output entity in the first set of benchmark output entities. 4. The method of claim 1, further comprising, assigning weights to each benchmark output entity to generate a weighted benchmark output entity; and wherein the comparison includes matching a first knowledge canvassing system output entity in a first set of knowledge canvassing system output entities to a first weighted benchmark output entity in a first set of weighted benchmark output entities. 5. The method of claim 1, further comprising aggregating the evaluation scores. 6. The method of claim 5, wherein aggregating the evaluation scores includes, averaging the evaluation scores. 7. The method of claim 1, further comprising training the knowledge canvassing system based on the evaluation scores. 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 training the knowledge canvassing system, the training system configured to: generate benchmark data, each benchmark datum including a set of one or more benchmark input entities and a set of one or more benchmark output entities associated with the one or more benchmark input entities; query the knowledge canvassing system with each set of benchmark input entities; receive, for each set of benchmark input entities queried, an output result from the knowledge canvassing system that includes a set of zero or more knowledge canvassing system output entities; and generate an evaluation score for each set of knowledge canvassing system output entities based on a comparison of the knowledge canvassing system output entities with the set of benchmark output entities. 9. The system of claim 8, wherein the training system is further configured to assign weights to each benchmark output entity to generate a weighted benchmark output entity for each benchmark output entity; and wherein the comparison includes matching a first knowledge canvassing system output entity in a first set of knowledge canvassing system output entities to a first weighted benchmark output entity in a first set of weighted benchmark output entities. 10. The system of claim 9, wherein the evaluation score increases for the first set of knowledge canvassing system output entities in response to the weight of the first weighted benchmark output entity increasing. 11. The system of claim 8, wherein the evaluation score is further based on an estimation of a degree to which an unmatched knowledge canvassing system output entity in the first set of knowledge canvassing system output entities relates to any benchmark output entity in a first set of benchmark output entities. 12. The system of claim 11, wherein the evaluation score includes a summary coverage score and a maximum coverage score, the maximum coverage score being based on a size of a first set of benchmark output entities. 13. The system of claim 12, wherein the summary coverage score is related to a percentage of benchmark output entities matched by a first set of knowledge canvassing system output entities. 14. The system of claim 11, wherein the estimation of degree to which an unmatched knowledge canvassing system output entity in the first set of knowledge canvassing system output entities relates to any benchmark output entity in a first set of benchmark output entities is based on proximity in a knowledge graph. 15. A computer program product for training 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: generate benchmark data, each benchmark datum including a set of one or more benchmark input entities and a set of one or more benchmark output entities associated with the one or more benchmark input entities; query the knowledge canvassing system with each set of benchmark input entities; receive, for each set of benchmark input entities queried, an output result from the knowledge canvassing system that includes a set of zero or more knowledge canvassing system output entities; and generate an evaluation score for each set of knowledge canvassing system output entities based on a comparison of the knowledge canvassing system output entities with the set of benchmark output entities. 16. The computer program product of claim 15, wherein the program instructions are further executable by the computer to cause the computer to assign weights to each benchmark output entity to generate a weighted benchmark output entity for each benchmark output entity; and wherein the comparison includes matching a first knowledge canvassing system output entity in a first set of knowledge canvassing system output entities to a first weighted benchmark output entity in a first set of weighted benchmark output entities. 17. The computer program product of claim 15, wherein the evaluation score is further based on an estimation of a degree to which an unmatched knowledge canvassing system output entity in the first set of knowledge canvassing system output entities relates to any benchmark output entity in a first set of benchmark output entities. 18. The computer program product of claim 17, wherein the evaluation score includes a summary coverage score and a maximum coverage score, the maximum coverage score being based on a size of a first set of benchmark output entities. 19. The computer program product of claim 18, wherein the summary coverage score is related to a percentage of benchmark output entities matched by a first set of knowledge canvassing system output entities. 20. The computer program product of claim 17, wherein the estimation of degree to which an unmatched knowledge canvassing system output entity in the first set of knowledge canvassing system output entities relates to any benchmark output entity in a first set of benchmark output entities is based on proximity in a knowledge graph.