Triple

T3984658
Position Surface form Disambiguated ID Type / Status
Subject North London E86841 entity
Predicate contains P35 FINISHED
Object Wood Green
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
E485206 NE FINISHED

How this triple was built (4 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: [North London, contains, Wood Green]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wood Green
Context triple: [North London, contains, Wood Green]
  • A. Harlesden
    Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
  • B. 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.
  • C. Leytonstone
    Leytonstone is a suburban district in East London, England, known for its residential character, local high street, and association with filmmaker Alfred Hitchcock.
  • D. Crouch End
    Crouch End is a leafy, affluent residential district in north London known for its village-like atmosphere, independent shops, and vibrant arts and café culture.
  • E. Kentish Town
    Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wood Green
Triple: [North London, contains, Wood Green]
Generated description
Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wood Green
Target entity description: Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
  • A. Harlesden
    Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
  • B. 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.
  • C. Leytonstone
    Leytonstone is a suburban district in East London, England, known for its residential character, local high street, and association with filmmaker Alfred Hitchcock.
  • D. Crouch End
    Crouch End is a leafy, affluent residential district in north London known for its village-like atmosphere, independent shops, and vibrant arts and café culture.
  • E. Kentish Town
    Kentish Town is a residential and commercial district in north London known for its vibrant high street, music venues, and proximity to central London.
  • F. None of above. chosen

Provenance (5 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9de58d48190969f354a1bf0df94 completed March 9, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69be89b9fcbc8190868b8d0584e94118 completed March 21, 2026, 12:06 p.m.
NEDg Description generation batch_69be8b54b7648190a32236301384a54f completed March 21, 2026, 12:13 p.m.
NED2 Entity disambiguation (via description) batch_69be8ba6dc4c81909a64f409bd18aa63 completed March 21, 2026, 12:14 p.m.
Created at: March 9, 2026, 3:33 p.m.