Triple

T10422801
Position Surface form Disambiguated ID Type / Status
Subject John Norton E245700 entity
Predicate hasFamilyName P18 FINISHED
Object Norton E89028 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: Norton | Statement: [John Norton, hasFamilyName, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton
Context triple: [John Norton, hasFamilyName, Norton]
  • A. Norton
    Norton is a dark-skinned American grape variety, historically significant in Midwestern and Eastern U.S. winemaking for producing deeply colored, full-bodied red wines with notable disease resistance.
  • B. Norton chosen
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • C. Norton
    Norton is a village in Gloucestershire, England, situated near the River Chelt and close to the town of Cheltenham.
  • D. Norton
    Norton is a residential suburb within the town of Runcorn in Cheshire, England.
  • E. Norton
    Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea2cd0788190b904ccdc251a9b7a completed April 7, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2160208190b6384190d9537df4 completed April 9, 2026, 7:21 p.m.
Created at: April 6, 2026, 12:12 p.m.