Abstract: In some NLP systems, queries are compared to different data sources stored in a corpus to provide an answer to the query. However, the best data sources for answering the query may not currently be contained within the corpus or the data sources in the corpus may contain stale data that provides an inaccurate answer. When receiving a query, the NLP system may evaluate the query to identify a data source that is likely to contain an answer to the query. If the data source is not currently contained within the corpus, the NLP system may ingest the data source. If the data source is already within the corpus, however, the NLP may determine a time-sensitivity value associated with at least some portion of the query. This value may then be used to determine whether the data source should be re-ingested—e.g., the information contained in the corpus is stale.

Abstract: System, computer-implemented method, and computer program product to receive a case by a deep question answering system, identify a policy relevant in generating a response to the case, the policy containing a set of criteria used in generating the response to the case, produce, by a first annotator, of a set of annotators, one or more relevant passages of the case, compute a criteria score for a first criterion, of the set of criteria, based on the one or more relevant passages of the case, an determine that the first criterion is met by the case when the criteria score for the first criterion exceeds a predefined threshold.