Triple

T16858788
Position Surface form Disambiguated ID Type / Status
Subject Alexandra Park E409854 entity
Predicate near P350 FINISHED
Object Wood Green NE ONNED1

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wood Green | Statement: [Alexandra Park, near, Wood Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wood Green
Context triple: [Alexandra Park, near, Wood Green]
  • A. Wood Green chosen
    Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
  • B. Harlesden
    Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
  • C. Willesden
    Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
  • D. Gospel Oak
    Gospel Oak is a residential district in north London, known for its proximity to Hampstead Heath and its mix of Victorian housing and council estates.
  • E. Leytonstone
    Leytonstone is a suburban district in East London, England, known for its residential character, local high street, and association with filmmaker Alfred Hitchcock.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b37ef4748190b149d98fc0ab4205 completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01954069e0819087fab0a782a83f39 finalizing May 11, 2026, 8:37 a.m.
Created at: April 10, 2026, 5:24 a.m.