Abstract: A system and method for generating a database query from a natural language using a query engine selector module for identifying appropriate database query format, a query engine builder module to generate appropriate database query using an intermediate query language 2 (IQL2) as input, and a data retriever module for fetching data from single or multiple data sources.

Abstract: The present disclosure discloses a system and method comprising a Natural Language Generation (NLG) module in a data visualization environment for generating a contextual narrative for visualization e.g. graphs in natural language. The narrative is generated using a composite system comprising business input, ontology structure comprising semantical relationship and a deep learning paraphrase model to express and enable semantics in a personalized manner. The essential element of the disclosure is the system and method for providing context to generated narrative, using ontology structure comprising semantic relationships and search criteria including, but not limited to, filters and types of aggregations.

Abstract: A system and method for generating a database query from a natural language using a query engine selector module for identifying appropriate database query format, a query engine builder module to generate appropriate database query using an intermediate query language 2 (IQL2) as input, and a data retriever module for fetching data from single or multiple data sources.

Abstract: A Machine Intelligence for Research and Analytics (MIRA) system and method for processing and retrieving relevant business insights with respect to a natural language-based query of a business user. The MIRA system comprises an encoder component wherein the first intermediate query language (IQL1) is an output of a NLP server engine of the MIRA system. A decoder component which involves second intermediate query language (IQL2), a reduced form of IQL1 obtained by displaying the IQL1 to the business user (in an interface) for additional user preferences and options by changing the elements of IQL 1 to obtain IQL2 as a direct interpretation (queried/aggregated) of the business user to the MIRA system.