Triple

T14679953
Position Surface form Disambiguated ID Type / Status
Subject Attleboro E344750 entity
Predicate hasNeighboringTown P3883 FINISHED
Object Norton E155744 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: [Attleboro, hasNeighboringTown, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton
Context triple: [Attleboro, hasNeighboringTown, Norton]
  • A. Norton
    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 chosen
    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 (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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5692284819090f775be8e478522 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde180ff0c8190a8b7c7804e36c3f8 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:27 a.m.