Triple

T20010178
Position Surface form Disambiguated ID Type / Status
Subject Billingham E494568 entity
Predicate locatedNear P294 FINISHED
Object Norton 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 | Statement: [Billingham, locatedNear, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton
Context triple: [Billingham, locatedNear, Norton]
  • A. Norton chosen
    Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
  • B. Norton
    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 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
    Norton is a village in Gloucestershire, England, situated near the River Chelt and close to the town of Cheltenham.
  • E. 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.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a81c5881909692fcaaf59a57c9 completed April 20, 2026, 5:26 p.m.
Created at: April 11, 2026, 3:33 p.m.