Triple

T15378188
Position Surface form Disambiguated ID Type / Status
Subject Harlesden E367724 entity
Predicate near P350 FINISHED
Object Willesden NE NERFINISHED

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: [Harlesden, near, Willesden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willesden
Context triple: [Harlesden, near, 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 (2 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e6044488190b0499db109f7f821 completed April 16, 2026, 1:41 a.m.
Created at: April 10, 2026, 3:19 a.m.