1. A system, comprising: a computer processor; and a memory containing a program that, when executed on the computer processor, performs an operation comprising: receiving first and second queries for processing by a natural language processing (NLP) system; identifying first and second data sources related to the first and second queries, respectively, by associating one or more elements of the first and second queries to the first and second data sources; and upon determining that the first related data source is not in a corpus of the NLP system, ingesting the first related data source into the corpus, wherein the corpus includes a data store comprising information from one or more data sources formatted and stored into one or more objects; and upon determining that the second related data source is in the corpus of the NLP system: before searching the second related data source for at least one answer to the second query, determining a time-sensitivity value associated with the second query indicating a degree to which an accurate answer to the second query is dependent on a staleness of the second related data source, and upon determining that the time-sensitivity value satisfies a staleness threshold, re-ingesting the second related data source into the corpus.
1. A system, comprising: a computer processor; and a memory containing a program that, when executed on the computer processor, performs an operation comprising: receiving first and second queries for processing by a natural language processing (NLP) system; identifying first and second data sources related to the first and second queries, respectively, by associating one or more elements of the first and second queries to the first and second data sources; and upon determining that the first related data source is not in a corpus of the NLP system, ingesting the first related data source into the corpus, wherein the corpus includes a data store comprising information from one or more data sources formatted and stored into one or more objects; and upon determining that the second related data source is in the corpus of the NLP system: before searching the second related data source for at least one answer to the second query, determining a time-sensitivity value associated with the second query indicating a degree to which an accurate answer to the second query is dependent on a staleness of the second related data source, and upon determining that the time-sensitivity value satisfies a staleness threshold, re-ingesting the second related data source into the corpus. 3. The system of claim 1 , wherein identifying the first and second related data sources further comprises: parsing each first and second queries to identify respective elements of each first and second queries that specifically provides the first and second data sources; characterizing the respective elements in each first and second queries by assigning respective topics to the respective elements; and identifying the first and second related data sources by comparing the topics to a plurality of topics associated with different data sources.