Seriously, does any programmer have the time to decipher byzantine shit like this before writing a new feature? "Custom local search", US 8255379 B2 > CLAIMS(

Seriously, does any programmer have the time to decipher byzantine shit like this before writing a new feature? "Custom local search", US 8255379 B2 > CLAIMS(20) A method comprising: receiving a query that is configured by an issuer of the query to perform a local search, wherein the local search is performed over a first dataset and a second data set, wherein the first dataset comprises a first entity and the second dataset comprises a second entity, and wherein the query comprises a first token and a second token; parsing the query such that the first token of the query is mapped to the first entity in the first dataset and the second token of the query is mapped to the second entity in the second dataset; and returning search results based at least in part upon the parsing of the query, wherein the method is executed by a processor of a computing device. 2. The method of claim 1, wherein the first dataset is a custom dataset, wherein the custom dataset comprises a plurality of entities generated by an end user, and wherein the plurality of entities comprise attributes that describe the plurality of entities and shapes pertaining to the plurality of entities. 3. The method of claim 2, wherein the second dataset comprises street-level vector data. 4. The method of claim 3, wherein parsing the query comprises determining an approximate geographic region pertaining to the query. 5. The method of claim 4, further comprising determining the approximate geographic region pertaining to the query based at least in part upon mapping the second token of the query to the second entity in the dataset. 6. The method of claim 1, wherein parsing the query comprises identifying which words and phrases in the query correspond to attributes in the first dataset and the second dataset. 7. The method of claim 1, wherein parsing the query comprises generating a plurality of different partial interpretations of the query. 8. The method of claim 7, wherein each partial interpretation in the plurality of partial interpretations comprises a set of mappings between tokens in the query to attributes in the first dataset and the second dataset and an approximate region of interest pertaining to the query. 9. The method of claim 8, further comprising refining at least one partial interpretation, wherein the at least one partial interpretation is refined by way of spatial processing. 10. The method of claim 9, wherein the at least one partial interpretation is refined by determining that an entity in the first dataset spatially corresponds with a region of interest pertaining to the query. 11. The method of claim 10, wherein the region of interest is altered based at least in part upon a geographic overlap of a previous region of interest and an entity. 12. The method of claim 1, wherein the query is received in a first language, and further comprising translating at least a portion of the query to a second language. 13. The method of claim 1, wherein the query is a free-form text query that comprises misspelled terms, erroneous terms, out of order terms, or valid but wrong terms. 14. A system that facilitates custom local search, the system comprising: a processor; and a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising: a receiver component that receives a query from a user, wherein the query comprises a plurality of tokens, wherein the query is configured to retrieve custom content with respect to a particular geographic region, and wherein the query comprises a first token and a second token; and an interpreter component that parses the query such that the first token is mapped to a first entity in a first dataset and the second token is mapped to a second entity in a second dataset, wherein the first dataset is a custom dataset that comprises custom data provided by an end user and the second dataset is a contextual dataset that comprises street-level geographic data. 15. The system of claim 14, wherein the first entity comprises a shape that describes a geographic region pertaining to the first entity, an attribute that describes the first entity, and a unique identifier that identifies the entity. 16. The system of claim 14, wherein the query comprises at least one token that is indicative of a custom dataset amongst a plurality of custom datasets to which the query pertains, free-form text, and at least one token that is indicative of geographic scope pertaining to the query. 17. The system of claim 14, wherein the interpreter component comprises a query interpreter component that outputs multiple partial interpretations of the query, wherein each partial interpretation comprises a list of mappings between subsequences of tokens of the query and sets of entities in the custom dataset and the contextual dataset and an approximate region of interest pertaining to the partial query interpretation. 18. The system of claim 17, wherein the interpreter component further comprises a refinement component that refines at least one of the partial interpretations, wherein the refinement component modifies the approximate region of interest pertaining to the partial query interpretation when refining the at least one of the partial interpretations. 19. The system of claim 18, wherein the interpreter component further comprises a ranker component that ranks refined partial interpretations. 20. A computer-readable data storage device comprising instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a query, wherein the query comprises a plurality of tokens, wherein the query is configured to execute over one or more custom datasets and one or more contextual datasets; generating a partial interpretation of the query, wherein generating the partial interpretation of the query comprises mapping a first subsequence of the tokens to a first attribute in the custom dataset and mapping a second subsequence of the tokens to a second attribute in the contextual dataset; refining the partial interpretation of the query to generate a refined interpretation, wherein refining the partial interpretation comprises mapping a first entity in the custom dataset that has the first attribute to the first subsequence of the tokens and mapping a second entity in the contextual dataset that has the second attribute to the second subsequence of tokens; and causing graphical items representative of the first entity and the second entity to be displayed on a display screen of a computing device. There should be a non-profit organization that files arbitrary new patents preemptively on behalf of the public and then release them into the public domain.