Triple

T8236552
Position Surface form Disambiguated ID Type / Status
Subject Chris Grayling E192422 entity
Predicate familyName P18 FINISHED
Object Grayling E256122 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: Grayling | Statement: [Chris Grayling, familyName, Grayling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grayling
Context triple: [Chris Grayling, familyName, Grayling]
  • A. Grayling chosen
    Grayling is a small city in northern Michigan known as a gateway to outdoor recreation in the surrounding forests, rivers, and lakes.
  • B. Graydon
    Graydon is a surname of English and Irish origin borne by various notable individuals, including those in politics, sports, and the arts.
  • C. Graveley
    Graveley is a small village and civil parish in the county of Hertfordshire in England.
  • D. Willow Bay
    Willow Bay is an American television journalist, author, and former model who has worked as a news anchor for major networks and later became dean of the USC Annenberg School for Communication and Journalism.
  • E. Terling
    Terling is a small rural village and civil parish in the county of Essex in eastern England, known for its historic buildings and countryside setting.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb782a5e18819096235679f5a644a8 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd34fb069c8190965d69fae908482e completed April 1, 2026, 3:08 p.m.
Created at: March 30, 2026, 5:47 p.m.