Triple

T16946142
Position Surface form Disambiguated ID Type / Status
Subject Hankou–Canton Railway E411073 entity
Predicate endPoint P390 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: [Hankou–Canton Railway, endPoint, Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton
Context triple: [Hankou–Canton Railway, endPoint, Canton]
  • A. Canton
    Canton is a small New England town in Hartford County, Connecticut, known for its historic village centers and scenic Farmington River setting.
  • B. Canton
    Canton is a city in northeastern Ohio best known as the home of the Pro Football Hall of Fame.
  • C. Canton
    Canton is a small city in southeastern South Dakota that serves as the county seat of Lincoln County.
  • D. Canton chosen
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • E. Canton
    Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cfb25e0c8190948e62d9575ae9cd completed April 18, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfeca4208190a3b9270869063d3d completed May 10, 2026, 6:35 p.m.
Created at: April 10, 2026, 5:31 a.m.