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Info

  • Every artifact created in Luma Knowledge through a source document or Web URL goes through the Semantic Analysis process of QnA pair generation and metadata identification.

  • An artifact created manually using Regular Template (Mini artifact) Template or FAQ Template, bypasses the QnA pair generation step. The system treats the manually created Artifact or FAQ as they are and doesn't try to find QnA pairs. The process only identifies metadata for the artifact.

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The status timeline is a visual representation of Sub flows that are triggered as part of the Semantic Analysis of an artifact. The illustration shows the sub-flow in execution, current status, and timestamp when the process is triggered.

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FAQ Generation is also called Question-Answering Analysis. The process is intended to determine the questions that can be answered by the source document. On 'Status Timeline', Curator can view FAQ Generation process status and start time.

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Luma Knowledge uses Azure QnA maker to generate these Question answer pairings. Each QnA pair generated through the process becomes a FAQ child Artifacts linked to the artifactParent Knowledge Artifact. In the case of FAQ generation processes encounter an error, the Semantic Analysis process is process fails, and the next steps are not executed. The timeline is updated appropriately to indicate the error.

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Info

Luma Knowledge uses QnA maker to generate FAQs, so the process is dependent on the product limitations. The process fails in case, Source document :

is not in

For successful QnA pair generation, the source document:

  • should follow Question-Answer format.

  • contains images.

  • document size is more than the permissible limit (up to 5 MB).

  • the document type is not allowed.

Metadata Generation

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  • should be in a supported document format such as .docx, pdf, .xlsx, txt.

  • should be within the permissible document size limit. This is configurable for each document type at the tenant level. Refer to Tenant Configurations for more information.

Ontology Generation

Ontology generation is intended to extract metadata from the document. Metadata represents key information (terms or phrases) that describes the artifact. It enhances searches for artifacts and assists the curation process by identifying known terms. NLP engine parses the document and identifies metadata elements for the Artifact and QnA pairs, using parts of speech and dependency rules. The identified meta-data is then normalized and can be used as search metadata for the artifact. 

Info

Artifact Name and Summary are used to generate Ontology for the Artifact.

Below are the metadata elements that are identified for each artifact:

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On 'Status Timeline', Curator can view the Ontology Generation process status and start time.

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In this step, Knowledge Ontology is generated for the Artifact and the QnA pairs. Each QnA pair with the identified metadata becomes a FAQ in Luma Knowledge and is related to the artifact.
Info

If the identified Topics are not present in the Knowledge Graph,

those

the Artifact is directly linked to the Domain selected at Artifact creation. The identified topics are added

as

to '

Identified terms

Suggested Metadata'.

Persistence

The last step in the Semantic Analysis process is Persistence. In this step, all the information identified and created in the earlier steps is saved into Luma Knowledge databases. Luma Knowledge uses three databases to save and maintain information in the system:

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Once the FAQ and metadata are generated, the information is pushed to databases. On 'Status Timeline', Curator can view the Persistence process status and start time.

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