# Q4a · Mention-pair coreference

Subject: Natural Language Processing

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/nlp/#tee/papers/legacy-f22/q4a

Canonical: https://deep-learning-study-room.vercel.app/read/nlp/tee/papers/legacy-f22--q4a/

Previous examination · complete worked answers

**Question. Explain the mention-pair model with a detailed example.** [10 marks]

### Answer

A mention is a span referring to an entity. A mention-pair model classifies a pair (earlier candidate antecedent, later mention) as coreferent or not. Pairwise decisions are subsequently linked into entity clusters; a positive score alone does not ensure globally consistent clusters.

Detect mentions → Generate earlier candidate pairs → Extract pair features → Score same-entity relation → Select/link antecedents → Form entity clusters

1. Text: “Rita bought a car. She likes it.” Detect Rita, a car, She, it.
2. For She, compare (Rita,She) and (a car,She). Features include person/number compatibility, animate type, syntactic role, sentence distance and lexical agreement.
3. Rita–She has compatible singular human features; car–She fails the ordinary inanimate reading. Select Rita.
4. For it, compare earlier mentions: car–it is singular/inanimate and contextually fits likes. Cluster {Rita,She} and {a car,it}.
5. Train a classifier on labelled mention pairs; at prediction, choose a sufficiently supported antecedent or leave a new entity. Avoid reflexive/binding violations and document leakage during evaluation.

Advantages: interpretable pair features and supervised learning. Limitations: quadratic candidate growth, error propagation from mention detection, non-transitive pair predictions, and weak long-range/world-knowledge reasoning. A greedy nearest-candidate choice is not the same as a learned mention-pair model.