Triple

T6408613
Position Surface form Disambiguated ID Type / Status
Subject Donny E127650 entity
Predicate basedIn P40 FINISHED
Object Doncaster E123073 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: Doncaster | Statement: [Donny, basedIn, Doncaster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doncaster
Context triple: [Donny, basedIn, Doncaster]
  • A. Doncaster chosen
    Doncaster is a large town and metropolitan borough in South Yorkshire, England, known historically for its railway heritage, horse racing, and role as a regional commercial center.
  • B. Yorkton
    Yorkton is a small city in southeastern Saskatchewan, Canada, known as a regional hub for agriculture and services.
  • C. Scunthorpe
    Scunthorpe is an industrial town in North Lincolnshire, England, historically known for its steel production.
  • D. Wakefield
    Wakefield is a historic cathedral city in West Yorkshire, Northern England, known for its medieval heritage and role as an administrative and commercial center in the region.
  • E. Wakefield
    Wakefield is a small rural township in New Zealand’s Tasman District, located southwest of Nelson and serving as a local service and farming community.
  • 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_69c0083723d88190b1e37b19df162c08 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068cdf25881908d42a5d979637ad6 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640c141548190b76a21e873c9147d completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:41 p.m.