Triple

T19957908
Position Surface form Disambiguated ID Type / Status
Subject Norton E479732 entity
Predicate notableModel P1503 FINISHED
Object Norton ES2 NE NERFINISHED

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 ES2 | Statement: [Norton, notableModel, Norton ES2]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton ES2
Context triple: [Norton, notableModel, Norton ES2]
  • A. Norton
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • B. Norton
    Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
  • C. 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.
  • D. Norton chosen
    Norton is a historic British motorcycle manufacturer renowned for its success in mid-20th-century road racing and the Isle of Man TT.
  • 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 (2 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65af1b32c81908ebe0e2570ec06a9 completed April 20, 2026, 4:57 p.m.
Created at: April 10, 2026, 1:54 p.m.