Guide-linked quiz · Medium Level
Entity Linking and Disambiguation Quiz
Test mention detection, context, candidate generation, bi-encoder retrieval, cross-encoder reranking, NIL outputs, and document-level coherence.
Question 1 of 8
What does entity linking connect a text mention to?
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Answers and explanations appear as you take the quiz.
- What does entity linking connect a text mention to?
- A random web page
- A new training run
- A spelling correction
- A unique entry in a knowledge base
- In the phrase 'the company Apple released a phone', what is the disambiguation task?
- Deciding Apple means the fruit, not the company
- Deciding Apple means the tech company, not the fruit
- Translating Apple into another language
- Counting the letters in Apple
- What is the purpose of the candidate generation stage?
- To write a new article
- To delete ambiguous words
- To retrieve a shortlist of possible matching entities
- To translate the text
- What role does a bi-encoder play in modern entity linking?
- Fast retrieval via separate embeddings for mention and entities
- Slow manual labeling of every mention
- Generating images of entities
- Encrypting the knowledge base
- What does a NIL class represent in entity linking?
- The most popular entity
- A mention with no matching knowledge-base entry
- A duplicate entity
- A training error
- How can document-level coherence help an entity-linking system?
- By guaranteeing that every mention has the same entity identifier
- By proving every document discusses only one topic
- By removing the need to evaluate individual mention contexts
- By considering whether candidate assignments fit the document context and one another
- After fast candidate retrieval, what information does a cross-encoder jointly read for entity-linking reranking?
- The mention's context and a candidate entity's description
- Only the entity's numeric identifier with no text
- Only the two input filenames
- Only the number of images in the knowledge base
- If an entity-linking pipeline never proposes the span 'Apple' for analysis, which initial stage has missed that mention?
- The final candidate reranker only
- The image-compression stage
- Mention detection
- The knowledge base's output filename formatter
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