Triple

T12075481
Position Surface form Disambiguated ID Type / Status
Subject Cheetham Hill E287533 entity
Predicate adjacentTo P224 FINISHED
Object Harpurhey E96876 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: Harpurhey | Statement: [Cheetham Hill, adjacentTo, Harpurhey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harpurhey
Context triple: [Cheetham Hill, adjacentTo, Harpurhey]
  • A. Harpurhey chosen
    Harpurhey is an inner-city district of Manchester, England, known for its dense residential areas and local shopping precincts.
  • B. Agbani
    Agbani is a town in southeastern Nigeria known as an educational and administrative hub within Enugu State.
  • C. Zaria Local Government Area
    Zaria Local Government Area is an administrative region in Kaduna State, Nigeria, centered on the historic city of Zaria, a major Hausa-Fulani cultural and commercial hub.
  • D. Ikoyi
    Ikoyi is an affluent, high-end residential and commercial district in Lagos, Nigeria, known for its luxury real estate, upscale hotels, and diplomatic presence.
  • E. Lekki
    Lekki is a fictional companion mascot character associated with Nokki, likely designed as a cute, supportive sidekick figure.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045ceeec81909427cae8972eed26 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f65ed5908190a0082796366a8825 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.