Triple

T3584684
Position Surface form Disambiguated ID Type / Status
Subject Yorkshire E75882 entity
Predicate contains P35 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: [Yorkshire, contains, Doncaster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doncaster
Context triple: [Yorkshire, contains, 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 suburban town in Middlesex County, Massachusetts, known for its commuter access to Boston and its scenic Lake Quannapowitt.
  • 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_69ad85d6dc3c8190b491b79b83e25461 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc10f9b508190bde4a4e4711dd452 completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503dbed588190abe9ca45b1ff68f8 completed March 14, 2026, 6:44 a.m.
Created at: March 8, 2026, 3:22 p.m.