Triple

T6263096
Position Surface form Disambiguated ID Type / Status
Subject British opium trade in China E140347 entity
Predicate tookPlaceIn P40 FINISHED
Object Canton E55203 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: Canton | Statement: [British opium trade in China, tookPlaceIn, Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton
Context triple: [British opium trade in China, tookPlaceIn, 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 historic waterfront neighborhood in southeast Baltimore, Maryland, known for its revitalized harborfront, rowhouses, and vibrant bar and restaurant scene.
  • D. Canton
    Canton is a small New England town in Hartford County, Connecticut, known for its historic village centers and scenic Farmington River setting.
  • E. Canton
    Canton is a city in northeastern Ohio best known as the home of the Pro Football Hall of Fame.
  • 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_69c008c95c5c819084bd3dd56133d84d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06387fec0819095b47a37b9402aa9 completed March 22, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c51932e704819083e1ed17a86f6b5e completed March 26, 2026, 11:32 a.m.
Created at: March 22, 2026, 4:25 p.m.