quiz.json

{
  "lesson": "25-entity-linking",
  "title": "Entity Linking & Disambiguation",
  "questions": [
    {
      "stage": "pre",
      "question": "What does entity linking add on top of NER?",
      "options": [
        "Translations",
        "Sentiment polarity",
        "Part-of-speech tags",
        "It maps each detected mention to a unique entry in a knowledge base (Wikidata, Wikipedia, or a domain KB)"
      ],
      "correct": 3,
      "explanation": "EL turns a mention into a canonical KB id, disambiguating between same-name entities."
    },
    {
      "stage": "pre",
      "question": "What are the two main subtasks in entity linking?",
      "options": [
        "Tokenization and parsing",
        "POS tagging and lemmatization",
        "Embedding and clustering",
        "Candidate generation (shortlist of plausible KB entries) and disambiguation (pick the right one given context)"
      ],
      "correct": 3,
      "explanation": "EL decomposes into proposing candidates then ranking them by contextual fit."
    },
    {
      "stage": "check",
      "question": "Why must mention recall be reported alongside disambiguation accuracy?",
      "options": [
        "Mention recall is mandatory by GDPR",
        "Recall replaces precision",
        "Disambiguation cannot recover from missing candidates; the pipeline is bounded by candidate-generation recall",
        "Recall is required by spaCy"
      ],
      "correct": 2,
      "explanation": "If candidates miss the gold entity, no disambiguator can fix it; recall floors pipeline quality."
    },
    {
      "stage": "check",
      "question": "How does GENRE perform entity linking?",
      "options": [
        "Decodes the entity's canonical name token-by-token under constrained decoding over a trie of valid KB ids",
        "By BM25",
        "By computing TF-IDF",
        "By PageRank"
      ],
      "correct": 0,
      "explanation": "GENRE generates the canonical KB name with constrained decoding to guarantee a valid id."
    },
    {
      "stage": "check",
      "question": "What is NIL handling in entity linking?",
      "options": [
        "Predicting a 'not in KB' label when no candidate is a real match (emerging entities, obscure people)",
        "Returning the entire candidate list",
        "Lowercasing the input",
        "Skipping every mention"
      ],
      "correct": 0,
      "explanation": "NIL prediction prevents guessing wrong KB ids for entities the KB does not cover."
    },
    {
      "stage": "post",
      "question": "Why does popularity bias hurt entity linking in specialized domains?",
      "options": [
        "Models trained on web data over-predict frequent entities (e.g. basketball Jordan over the ML researcher Michael I. Jordan)",
        "It biases toward older entities only",
        "Popularity removes NIL",
        "Popularity helps recall"
      ],
      "correct": 0,
      "explanation": "Popularity priors skew predictions away from less-common, domain-specific name-clashes."
    },
    {
      "stage": "post",
      "question": "What is a safe LLM-EL pattern in 2026?",
      "options": [
        "Provide a candidate list and use constrained JSON output that the LLM can only choose from valid KB ids",
        "Just prompt 'find the entity'",
        "Free-form generation",
        "Skip candidate generation"
      ],
      "correct": 0,
      "explanation": "Constraining the LLM to a valid candidate list prevents made-up KB ids and keeps output queryable."
    },
    {
      "stage": "post",
      "question": "Why must NER mention boundaries be exact for entity linking to work?",
      "options": [
        "Boundary errors propagate: 'Bank of America' clipped to 'Bank' surfaces wrong candidates and tanks EL recall",
        "Boundary precision only affects NER metrics, not entity-linking candidate quality",
        "Boundaries change tokenization",
        "Boundaries break Wikipedia lookups"
      ],
      "correct": 0,
      "explanation": "Mis-bounded mentions retrieve the wrong alias set, propagating errors into disambiguation."
    }
  ]
}