What are the steps involved in the AI enrichment pipeline of Azure Cognitive Search? (Select three answer choices)
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A. B. C. D. E.Correct Answers: A, B and C.
Option A is correct because connect and document cracking phase enable to connect with the data source and cracking source documents to extract text from non-text sources.
Option B is correct because the cognitive skills and enrichment phase enable to perform cognitive skills such as entity recognition and key-phrase extraction.
Option C is correct because the search index provides query-based access when the processing is finished, and you have a search index consisting of enriched documents.
Option D is incorrect because this action is needed for optimizing indexing with the push API.
It is not a step involved in the AI enrichment pipeline.
Option E is incorrect because this action is executed while building a Search-enabled website using .NET.
It is not a step involved in the AI enrichment pipeline.
Reference:
To learn more about the AI enrichment pipeline, use the link given below:
The AI enrichment pipeline of Azure Cognitive Search consists of several steps that enable the extraction of valuable insights from unstructured data. The steps involved in this pipeline are:
Connect and document cracking: The first step is to connect to the data source and extract the unstructured data. This data can be in the form of documents, images, or videos. The documents are then processed using document cracking techniques to extract the text and metadata.
Cognitive skills and enrichment: The extracted text and metadata are then passed through cognitive skills, which are pre-built or custom-built algorithms that can analyze the data and extract meaningful insights. The cognitive skills can perform tasks such as language detection, sentiment analysis, entity recognition, key phrase extraction, and more.
Search index and provide query-based access: The enriched data is then indexed and made searchable using Azure Search. The search index is created based on the schema of the enriched data, and queries can be performed against the index to retrieve relevant results.
Therefore, the correct answer choices are A, B, and C: Connect and document cracking, Cognitive skills and enrichment, and Search index and provide query-based access.
Options D and E are not part of the AI enrichment pipeline of Azure Cognitive Search. Using multiple threads to increase indexing speeds is a performance optimization technique that can be applied during the indexing process. Creating a search resource with the VS Code extension is a step that can be performed before or after the AI enrichment pipeline, depending on the requirements of the solution.