Distributed queries in form of natural language can be very versatile and useful for analytics in Big Data. Linked Data in form of a data lake can provide a way to semantically produce natural language questions that are then translated into queries especially in form of SPARQL. However, such approaches can further be extended into other types of queries. Natural Language Generation is another aspect of such conversion and tranformation steps. Often such approaches are replicated in a search engine or in semantic web where tokenized words are exposed using subject-predicate-object that are linked to a relative URI reference that map to an ontology schema such as from a custom knowledgebase like DBPedia. An application of such an implementation approach can be found in Quepy which uses transformations and semantic relations.
