AI-102 Practice Question: Implement natural language processing solutions
A legal firm uses Azure AI Language's custom NER to extract party names, dates, and clauses from contracts. The model performs well on English contracts but poorly on French contracts. The firm wants to improve performance without retraining from scratch. What is the most efficient approach?
⚠ Common exam trap
A common pitfall in the AI-102 exam is assuming you must train separate models for each language or rely on translation, when Azure AI Language's built-in multilingual support is the correct and efficient path.
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
✓
Use the multilingual option in Azure AI Language custom NER to extend the existing project to include French.
Azure AI Language's custom NER supports a multilingual option that allows you to extend an existing project to include additional languages without retraining from scratch. By enabling this option and adding French labeled data, the model learns to recognize entities in French while retaining its English performance, making it the most efficient approach.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a separate custom NER project for French and train from scratch using French contracts.
Why it's wrong here
Training a fresh French project discards the English model's learned entity schema and labelled data, which is exactly the from-scratch retraining the firm wants to avoid. Separate projects suit wholly unrelated domains or languages where no shared schema or transferable labels exist.
- ✗
Retrain the English model with a mix of English and French contracts.
Why it's wrong here
Retraining the English model on mixed-language data rebuilds the existing model, contradicting the requirement to avoid retraining from scratch and risking regression on English contracts. Mixing corpora is the right approach only when building a single multilingual model deliberately from the outset.
- ✗
Use Azure AI Translator to translate French contracts to English, then use the English model.
Why it's wrong here
Translating French contracts into English introduces terminology drift and loses French legal phrasing, degrading extraction accuracy on party names and clauses. Translator is the right choice for human-readable localisation or gisting, not for preserving entity fidelity in a custom NER pipeline.
- ✓
Use the multilingual option in Azure AI Language custom NER to extend the existing project to include French.
Why this is correct
Enabling the multilingual option extends the existing project's training to cover French alongside English, reusing the current labelled data and model rather than building and training a separate project from scratch, which is the most efficient route.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.