System and method for generating database queries based on natural language input

1 . A method for generating one or more database queries based on natural language input data, the method comprising:

configuring, using a conversational artificial intelligence (AI) editing module, information for completing a task-oriented dialogue based on natural language input data;

parsing the configured information based on a database schema;

generating a parsed database schema based on the parsed configured information;

generating, using a natural language question-answering system, one or more database queries based on the parsed database schema and the natural language input data;

obtaining at least one database entry from one or more databases by executing the one or more database queries;

comparing the at least one database entry with the configured information; and

generating a clarification prompt based on the comparison.

2 . The method of claim 1 , wherein the natural language question-answering system is a table question-answering (TableQA) system or a knowledge-graph question-answering system.

3 . The method of claim 1 , wherein the at least one database entry comprises a table, the table having at least one row and at least one column.

4 . The method of claim 3 , further comprising:

determining whether there are multiple possible values based on the natural language input data and the table of the at least one database entry.

5 . The method of claim 4 , further comprising:

determining there are multiple possible values; and

generating, using the natural language question-answering system, a clarification information based on the natural language input data.

6 . The method of claim 1 , wherein the natural language input data comprises at least one of a text-based data, an audio data, or any combination thereof.

7 . The method of claim 1 , wherein the database schema is Structured Query Language (SQL) database schema and the one or more database queries includes a SQL query.

8 . The method of claim 1 , further comprising:

parsing, using a resource description framework schema, the natural language input data, wherein the generated one or more database queries includes a SPARQL query.

9 . The method of claim 1 , wherein the conversational AI editing module comprises a chatbot dialogue flow editor module.

10 . The method of claim 1 , wherein generating the clarification prompt comprises:

revising the configured information, wherein the clarification prompt is based on the revised configured information.

11 . A system for generating one or more database queries based on natural language input data, the system comprises:

at least one memory storing instruction; and

at least one processor coupled to the at least one memory, the at least one processor is configured to execute the instructions to:

configure information for completing a task-oriented dialogue based on natural language input data;

parse the configured information based on a database schema;

generate a parsed database schema based on the parsed configured information;

generate, using a natural language question-answering system, one or more database queries based on the parsed database schema and the natural language input data;

obtain at least one database entry from one or more databases by executing the one or more database queries;

compare the at least one database entry with the configured information; and

generate a clarification prompt based on the comparison.

12 . The system of claim 11 , wherein the natural language question-answering system is a table question-answering (Table QA) system or a knowledge-graph question-answering system.

13 . The system of claim 11 , wherein the at least one database entry comprises a table, the table having at least one row and at least one column.

14 . The system of claim 13 , wherein the at least one processor is further configured to execute the instructions to:

determine whether there are multiple possible values based on the natural language input data and the table of the at least one database entry.

15 . The system of claim 14 , wherein the at least one processor is further configured to execute the instructions to:

determine there are multiple possible values; and

generate, using the natural language question-answering system, a clarification information in response to the natural language input data.

16 . The system of claim 14 , wherein the natural language input data comprises a text-based data, an audio data, or any combination thereof.

17 . The system of claim 14 , wherein the database schema is Structured Query Language (SQL) database schema and the one or more database queries include a SQL query.

18 . The system of claim 14 , wherein the at least one processor is further configured to execute the instructions to:

parse, using a resource description framework schema, the natural language input data, wherein the generated one or more database queries include a SPARQL query.

19 . The system of claim 14 , wherein to generate the clarification prompt, the at least one processor is further configured to execute the instructions to:

revise the configured information, wherein the clarification prompt is based on the revised configured information.

20 . A non-transitory computer-readable medium comprising program instructions, which, when executed by one or more processors, cause the one or more processors to perform operations comprising:

configuring information for completing a task-oriented dialogue based on natural language input data;

parsing the configured information based on a database schema;

generating a parsed database schema based on the parsed configured information;

generating, using a natural language question-answering system, one or more database queries based on the parsed database schema and the natural language input data;

retrieving, from an associated database, at least one database entry by executing the one or more database queries;

comparing the at least one database entry with the information for the task-oriented dialogue; and

generating a clarification prompt based on the comparison.