Systems and methods for disambiguation of agricultural input are disclosed. An example disclosed method includes determining a first probability for a second product specifier. The first probability indicates a likelihood that the second product specifier is correct. Additionally, the example method includes, in response to determining that agricultural input identifiers for a manufacturer associated with a portion of the first product specifier are in a variety database, modifying the first probability with a second probability. The example method includes, in response to determining that the agricultural input identifiers for the manufacturer associated with the portion of the first product specifier are not in the variety database, modifying the first probability with a third probability different from the second probability. The example method includes comparing the modified first probability with a threshold, and associating the second product specifier with the vehicle location when the modified first probability satisfies the threshold.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A vehicle activity data correction method comprising: receiving vehicle activity data from a vehicle, the vehicle activity data including a first product specifier and a vehicle location; generating a second product specifier, the second product specifier based on a transformation from the first product specifier; determining, with a processor, a first probability for the second product specifier, the first probability indicating a likelihood that the second product specifier is correct; in response to determining that agricultural input identifiers for a manufacturer associated with a portion of the first product specifier are in a variety database, modifying the first probability with a second probability; in response to determining that the agricultural input identifiers for the manufacturer associated with the portion of the first product specifier are not in the variety database, modifying the first probability with a third probability different from the second probability; comparing the modified first probability with a threshold; and associating the second product specifier with the vehicle location when the modified first probability satisfies the threshold. 2. The method of claim 1, including: setting the second probability to one when the second product specifier matches one of the agricultural input identifiers in the variety database associated with the manufacturer; and setting the second probability to zero when the second product specifier does not match one of the agricultural input identifiers in the variety database associated with the manufacturer. 3. The method of claim 1, including: determining a geographic probability; determining a field documentation probability; selecting one of the geographic probability or the field documentation probability to be the third probability. 4. The method of claim 3, wherein the geographic probability is based on a geographic neighborhood of the geographic location. 5. The method of claim 3, wherein the field documentation probability is based on records in a geographic database that include the second product specifier. 6. The method of claim 1, including generating the second product specifier is based on the first second product specifier received from a vehicle and a format associated with the manufacturer stored in the variety database. 7. The method of claim 6, wherein first probability is based on the transformation from the second product specifier to the first product specifier. 8. The method of claim 1, wherein the second product specifier identifies at least one of a seed, a fertilizer, or a pesticide. 9. The method of claim 1, including transmitting the second product specifier to the vehicle, the vehicle to modify of a dispersal rate of an agricultural product by the vehicle based on the second product specifier. 10. A product disambiguator to correct vehicle activity data comprising: a formatter to: receive the vehicle activity data from a vehicle, the vehicle activity data including a first product specifier and a vehicle location; generate a second product specifier, the second product specifier based on a transformation from the first product specifier; determine a second probability for the second product specifier, the first probability indicating a likelihood that the second product specifier is correct; and a normalizer to: in response to determining that agricultural input identifiers for a manufacturer associated with a portion of the first product specifier are in a variety database, modify the first probability with a second probability; in response to determining that the agricultural input identifiers for the manufacturer associated with the portion of the first product specifier are not in the variety database, modify the first probability with a third probability different from the second probability; compare the modified first probability with a threshold; and associate the second product specifier with the vehicle location when the modified first probability satisfies the threshold. 11. The product disambiguator of claim 10, including a catalog matcher to: set the second probability to one when the second product specifier matches one of the agricultural input identifiers in the variety database associated with the manufacturer; and set the second probability to zero when the second product specifier does not match one of the agricultural input identifiers in the variety database associated with the manufacturer. 12. The product disambiguator of claim 10, including: a geographic analyzer to determine a geographic probability; a count analyzer to determine a field documentation probability; wherein the formatter is to select one of the geographic probability or the field documentation probability to be the third probability. 13. The product disambiguator of claim 12, wherein the geographic probability is based on a geographic neighborhood of the geographic location. 14. The product disambiguator of claim 12, wherein the field documentation probability is based on records in a geographic database that include the second product specifier. 15. The product disambiguator of claim 10, wherein the formatter is to generate the second product specifier based on a second product specifier received from the vehicle and a format associated with the manufacturer stored in the variety database. 16. The product disambiguator of claim 15, wherein first probability is based on the transformation from the second product specifier to the first product specifier. 17. The product disambiguator of claim 10, wherein the second product specifier identifies at least one of a seed, a fertilizer, or a pesticide 18. A tangible computer readable medium comprising instructions that, when executed, cause a server to: receive vehicle activity data from a vehicle, the vehicle activity data including a first product specifier and a vehicle location; generate a plurality of second product specifiers, the second product specifiers based on a transformation from the first product specifier; determine a plurality of first probabilities for the corresponding plurality second product specifiers, the first probabilities indicating a likelihood that the corresponding second product specifier is correct; in response to determining that agricultural input identifiers for a manufacturer associated with a portion of the first product specifier are in a variety database, modify the plurality of first probabilities with a corresponding second probability; in response to determining that the agricultural input identifiers for the manufacturer associated with the portion of the first product specifier are not in the variety database, modify the plurality of first probabilities with a corresponding third probability different from the second probability; compare the modified first probabilities with a threshold; and associate the one of plurality of second product specifiers that satisfies the threshold with the vehicle location. 19. The tangible computer readable medium of claim 18, wherein the instructions, when executed, cause the server to: set the second probability to one when the corresponding one of the plurality of second product specifiers matches one of the agricultural input identifiers in the variety database associated with the manufacturer; and set the second probability to zero when the corresponding one of the plurality of second product specifiers does not match one of the agricultural input identifiers in the variety database associated with the manufacturer. 20. The tangible computer readable medium of claim 18, wherein the instructions, when executed, cause the server to, for the plurality of second product specifiers: determine a corresponding geographic probability; determine a corresponding field documentation probability; select one of the geographic probability or the field documentation probability to be the corresponding third probability. 21. The method of claim 20, wherein the geographic probability is based on a geographic neighborhood of the geographic location. 22. The tangible computer readable medium of claim 20, wherein the field documentation probability is based on records in a geographic database that include the product specifier. 23. The tangible computer readable medium of claim 18, wherein the instructions, when executed, cause the server to generate the second product specifier based on the first product specifier received from a vehicle and a format associated with the manufacturer stored in the variety database, the when the corresponding one of the plurality of first probabilities being based on a transformation from the first product specifier to the corresponding ones of the plurality of second product specifiers.