AI-102 Practice Question: Implement natural language processing solutions
A support team wants to build a bot that answers employee questions by using a set of internal HR policy documents. The team does not want to author question-and-answer pairs manually and needs the bot to return the most relevant passage from the documents, with the source cited. The documents are in English and are updated frequently in a blob container. Which Azure AI Language feature should the team use?
⚠ Common exam trap
Candidates often confuse question answering with intent classification, where only question answering stores documents and returns cited passages.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Custom question answering with a project that imports the documents and enables the option to extract answers from the source content
Custom question answering supports importing documents and automatically generating question-and-answer pairs, plus extracting answers directly from source content. It returns the best matching passage with a citation, and it can refresh from a blob container as documents change, meeting the no-manual-authoring and source-citation requirements.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Named Entity Recognition with a custom model trained on HR policies
Why it's wrong here
Named Entity Recognition extracts entities such as people, organizations, and dates. It does not answer questions or retrieve passages from documents, and it does not provide source citations. Training a custom model would only improve entity detection, which is unrelated to the goal of returning a relevant HR policy passage.
- ✗
Conversational language understanding with an intent for each HR topic
Why it's wrong here
Conversational language understanding predicts intents and extracts entities from user utterances. It does not store policy documents, retrieve passages, or provide citations. Building an intent per HR topic would require labeled utterances and would still not return the exact policy text, so it cannot satisfy the passage-with-source requirement.
- ✗
Custom text classification with a single-label project
Why it's wrong here
Custom text classification assigns a category label to text; it does not retrieve relevant passages or return source citations. It would require labeled training data and would output a class such as 'HR' or 'Payroll', which does not answer an employee question or point to a policy paragraph, so it is the wrong feature for passage retrieval.
- ✓
Custom question answering with a project that imports the documents and enables the option to extract answers from the source content
Why this is correct
Custom question answering can ingest documents, automatically generate question-and-answer pairs, and extract answers from the source content. It returns the best passage with a source citation, which matches the requirement to avoid manual authoring and to cite the document. It also supports refreshing the knowledge base when documents change.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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