METHOD AND SYSTEM OF GENERATING KNOWLEDGE GRAPH OF DATA REPOSITORY
A method ( 400 ) and system ( 100 ) of generating knowledge graph of the data repository is disclosed. The method ( 400 ) includes receiving input data ( 302 ) and access of data repository ( 304 ). The method ( 400 ) may include generating semantic ( 310 ) representation of data repository ( 304 ) schema based on input data ( 302 ) and data repository ( 304 ) using language model. The method ( 400 ) may further include validating semantic representation ( 310 ) syntactically and with respect to input data ( 302 ). The method ( 400 ) may further include generating mapping ( 320 ) file of data repository ( 304 ) schema based on semantic representation ( 310 ) and data repository ( 304 ) using language model. The mapping file ( 320 ) may include mapping of plurality of elements of semantic representation ( 310 ) to corresponding elements in input data ( 302 ). Further, the method ( 400 ) includes validating mapping file ( 320 ) syntactically and semantically based on semantic representation ( 310 ), data repository ( 304 ) and input data ( 302 ).
1 . A computer-implemented method of generating knowledge graph of a data repository, the computer-implemented method comprising:
receiving an input data and an access of the data repository;
generating a semantic representation of a data repository schema based on the input data and the data repository using a language model, wherein the semantic representation comprises a plurality of elements, and wherein the semantic representation incorporates domain or task specific logics;
validating the semantic representation syntactically and with respect to the input data;
generating a mapping file of the data repository schema based on the semantic representation and the data repository using the language model, wherein the mapping file comprises a mapping of the plurality of elements of the semantic representation to corresponding elements in the input data; and
validating the mapping file syntactically and semantically based on the semantic representation, data repository and the input data.
2 . The computer-implemented method of claim 1 , wherein the semantic representation is a graph-based or knowledge-based abstraction of the data repository schema.
3 . The computer-implemented method of claim 1 , wherein the domain or task specific logics are integrated into the semantic representation based on the input data and the validation of the semantic representation.
4 . The computer-implemented method of claim 1 , wherein the structural and syntactic integrity of the semantic representation and the mapping file is checked by a plurality of predefined rules.
5 . The computer-implemented method of claim 1 , wherein the language model is a large language model (LLM) trained to process structured prompts and domain knowledge.
6 . The computer-implemented method of claim 1 , wherein the semantic representation of the data repository schema is generated by a LLM based ontology generation agent, and wherein the mapping file of the data repository schema is generated by a LLM based mapping generation agent.
7 . The computer-implemented method of claim 1 , wherein the semantic representation and the mapping file are iteratively refined using feedback loops with the language model until the semantic representation and mapping file meets a predefined validation criterion, and wherein the feedback loops comprises one or more iterations of the validation of the semantic representation and the validation of the mapping file.
8 . A system of generating knowledge graph of a data repository, the system comprising:
a processor; and
a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, cause the processor to:
receive an input data and an access of the data repository;
generate a semantic representation of a data repository schema based on the input data and the data repository using a language model, wherein the semantic representation comprises a plurality of elements, and wherein the semantic representation incorporates domain or task specific logics;
validate the semantic representation syntactically and with respect to the input data;
generate a mapping file of the data repository schema based on the semantic representation and the data repository using the language model, wherein the mapping file comprises a mapping of the plurality of elements of the semantic representation to corresponding elements in the input data; and
validate the mapping file syntactically and semantically based on the semantic representation, data repository and the input data.
9 . The system of claim 8 , wherein the semantic representation is a graph-based or knowledge-based abstraction of the data repository schema.
10 . The system of claim 8 , wherein the domain or task specific logics are integrated into the semantic representation based on the input data and the validation of the semantic representation.
11 . The system of claim 8 , wherein the structural and syntactic integrity of the semantic representation and the mapping file is checked by a plurality of predefined rules.
12 . The system of claim 8 , wherein the language model is a Large Language Model (LLM) trained to process structured prompts and domain knowledge.
13 . The system of claim 8 , wherein the semantic representation of the data repository schema is generated by a LLM based ontology generation agent, and wherein the mapping file of the data repository schema is generated by a LLM based mapping generation agent.
14 . The system of claim 8 , wherein the semantic representation and the mapping file are iteratively refined using feedback loops with the language model until the semantic representation and mapping file meets a predefined validation criterion, and wherein the feedback loops comprises one or more iterations of the validation of the semantic representation and the validation of the mapping file.
15 . A non-transitory computer-readable storage medium having stored thereon computer executable instruction which when executed by one or more processors, cause the one or more processors to carry out a method of generating knowledge graph of a data repository, the method comprising:
receiving an input data and an access of the data repository;
generating a semantic representation of a data repository schema based on the input data and the data repository using a language model, wherein the semantic representation comprises a plurality of elements, and wherein the semantic representation incorporates domain or task specific logics;
validating the semantic representation syntactically and with respect to the input data;
generating a mapping file of the data repository schema based on the semantic representation and the data repository using the language model, wherein the mapping file comprises a mapping of the plurality of elements of the semantic representation to corresponding elements in the input data; and
validating the mapping file syntactically and semantically based on the semantic representation, data repository and the input data.
16 . The non-transitory computer-readable storage medium of claim 15 , wherein the semantic representation is a graph-based or knowledge-based abstraction of the data repository schema.
17 . The non-transitory computer-readable storage medium of claim 15 , wherein the domain or task specific logics are integrated into the semantic representation based on the input data and the validation of the semantic representation.
18 . The non-transitory computer-readable storage medium of claim 15 , wherein the structural and syntactic integrity of the semantic representation and the mapping file is checked by a plurality of predefined rules.
19 . The non-transitory computer-readable storage medium of claim 15 , wherein the language model is a large language model (LLM) trained to process structured prompts and domain knowledge.
20 . The non-transitory computer-readable storage medium of claim 15 , wherein the semantic representation and the mapping file are iteratively refined using feedback loops with the language model until the semantic representation and mapping file meets a predefined validation criterion, and wherein the feedback loops comprises one or more iterations of the validation of the semantic representation and the validation of the mapping file.