Triple

T19559225
Position Surface form Disambiguated ID Type / Status
Subject Harrow Road E489397 entity
Predicate historicallyAssociatedWith P2830 FINISHED
Object Willesden E598609 NE FINISHED

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: Willesden | Statement: [Harrow Road, historicallyAssociatedWith, Willesden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willesden
Context triple: [Harrow Road, historicallyAssociatedWith, Willesden]
  • A. Willesden chosen
    Willesden is a residential district in the London Borough of Brent, known for its diverse community and good transport links in northwest London.
  • B. Harlesden
    Harlesden is a residential district in northwest London known for its diverse community and strong Caribbean and Brazilian cultural influences.
  • C. Perivale
    Perivale is a suburban area in the London Borough of Ealing, known for its residential neighborhoods, industrial estates, and green spaces in west London.
  • D. Wood Green
    Wood Green is a busy urban district and major shopping and transport hub in the London Borough of Haringey in north London.
  • E. Yiewsley
    Yiewsley is a suburban area in the London Borough of Hillingdon in west London, known for its residential character and proximity to waterways and transport links.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f723d5081909553a4363b579a6b completed April 20, 2026, 3 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a9ea620f08190971672a93a2088d1 completed May 18, 2026, 5:07 a.m.
Created at: April 10, 2026, 1:42 p.m.