AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure
What is 'coreference resolution' in natural language processing?
⚠ Common exam trap
Test-takers frequently confuse 'coreference resolution' with 'entity extraction' (named entity recognition), but coreference resolution specifically links different mentions of the same entity, not just identifying the entity type.
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
✓
Identifying which words or phrases in a text refer to the same real-world entity
Coreference resolution is the NLP task of identifying when two or more expressions in a text refer to the same real-world entity. For example, in 'Alice said she would come,' the pronoun 'she' corefers to 'Alice.' This is fundamental for tasks like document summarization and question answering, where maintaining entity consistency is critical.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Checking whether a document's references (citations) are correctly formatted
Why it's wrong here
This is a document-level formatting task that verifies whether citations comply with a bibliographic style guide (e.g., APA, IEEE, MLA), using regular expressions or metadata matching rather than natural language understanding. Coreference resolution, by contrast, is a linguistic analysis that identifies whether two textual mentions—such as "she" and "Dr. Emily Carter"—point to the same real-world entity. Since citation checking does not involve resolving anaphoric references, this option is incorrect.
- ✓
Identifying which words or phrases in a text refer to the same real-world entity
Why this is correct
This is the foundational definition of coreference resolution. The model detects spans of text that mention an entity—including pronouns like "he," proper names like "Satya Nadella," and descriptions like "the CEO"—and groups them into clusters referring to the same real-world entity. This deep understanding enables downstream tasks such as question answering, document summarization, and entity linking to treat scattered mentions as one coherent object.
- ✗
Resolving conflicts when multiple languages are mixed in the same document
Why it's wrong here
Mixing languages in a document is a code-switching phenomenon, which involves language identification, language segmentation, and cross-lingual token alignment. Coreference resolution, in contrast, focuses on whether two expressions share the same referent regardless of surface form, and it does not resolve conflicts that arise from alternating grammatical systems. Code-switching is therefore an orthogonal NLP problem, making this option incorrect.
- ✗
Matching database foreign keys to their referenced primary keys
Why it's wrong here
Matching foreign keys to primary keys is a relational database referential-integrity constraint that ensures every foreign key value points to an existing primary key in another table. Coreference resolution, however, is a natural language processing technique applied to unstructured text, not to structured table columns. It resolves linguistic mentions like "it" to "server," rather than establishing key relationships, so this option is incorrect.
Go deeper
Related to this question
Learn chapter
Extractive vs Abstractive Text Summarisation
Key term
Question answering
Question answering is an Azure AI service that lets you build a natural language query system that extracts answers from a custom knowledge base of documents or FAQs.
Key term
Natural language processing
Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and respond to human language in a way that is both meaningful and useful.
About these practice questions
One of 985 original AI-900 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 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-900 exam.