Triple

T1742015
Position Surface form Disambiguated ID Type / Status
Subject Georgia Gold Belt E38253 entity
Predicate containsCity P294 FINISHED
Object Canton E166236 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: [Georgia Gold Belt, containsCity, Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canton
Context triple: [Georgia Gold Belt, containsCity, Canton]
  • A. Canton
    Canton is the historical Western name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • B. Canton chosen
    Canton is a suburban town in Norfolk County, Massachusetts, located southwest of Boston and known for its residential character and local historic sites.
  • C. Burlington
    Burlington is a historic city in present-day New Jersey that once served as the colonial capital of the Province of New Jersey.
  • D. Burlington
    Burlington is a mid-sized city in southern Ontario, Canada, located on the shores of Lake Ontario between Toronto and Hamilton.
  • E. Burlington
    Burlington is a suburban town in Massachusetts known for its proximity to Boston and its mix of residential neighborhoods, office parks, and retail centers.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c6d21c8190809bedaa798e2b14 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0dbc7c081909d637c5a482389ef completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:30 p.m.