Triple

T23194582
Position Surface form Disambiguated ID Type / Status
Subject Canton System E579839 entity
Predicate location P40 FINISHED
Object Canton 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: Canton | Statement: [Canton System, location, Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton
Context triple: [Canton System, location, Canton]
  • A. Canton chosen
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • B. Canton
    Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
  • C. Canton
    Canton is a small New England town in Hartford County, Connecticut, known for its historic village centers and scenic Farmington River setting.
  • D. Canton
    Canton is a city in northeastern Ohio best known as the home of the Pro Football Hall of Fame.
  • E. Canton
    Canton is a small city in southeastern South Dakota that serves as the county seat of Lincoln County.
  • 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_69e24600eed08190bd7e5295653a1503 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18fda64cc8190aeb5ccd8d8d20858 completed April 29, 2026, 4:58 a.m.
Created at: April 17, 2026, 4:06 p.m.