Triple

T5707859
Position Surface form Disambiguated ID Type / Status
Subject Trafford Training Centre E125829 entity
Predicate shortName P43 FINISHED
Object Carrington E315173 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: Carrington | Statement: [Trafford Training Centre, shortName, Carrington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carrington
Context triple: [Trafford Training Centre, shortName, Carrington]
  • A. Carrington
    Carrington is a surname of English origin borne by various notable individuals across politics, the military, the arts, and other fields.
  • B. Carrington chosen
    Carrington is a village in Greater Manchester, England, known for its industrial estates and proximity to the Manchester Ship Canal.
  • C. Carson
    Carson is a given name most famously associated with American novelist Carson McCullers, known for her works exploring loneliness and the human condition.
  • D. Carson
    Carson is the surname of Rachel Carson, the influential American marine biologist and conservationist whose writings advanced the global environmental movement.
  • E. Carson
    Carson is a suburban city in Los Angeles County, California, known for its diverse residential communities and proximity to major freeways and ports.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024892fd88190a91133fc88365410 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a6c17608190a9a808c2c77d937c completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:45 p.m.