Triple

T1176532
Position Surface form Disambiguated ID Type / Status
Subject Goodes Hall E25037 entity
Predicate city P40 FINISHED
Object Kingston E21878 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: Kingston | Statement: [Goodes Hall, city, Kingston]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kingston
Context triple: [Goodes Hall, city, Kingston]
  • A. Kingston chosen
    Kingston is a historic Canadian city in eastern Ontario, located where the St. Lawrence River meets Lake Ontario, known for its limestone architecture and role as a former capital of the Province of Canada.
  • B. Kingston
    Kingston is the largest city of Jamaica and its political, cultural, and economic center.
  • C. Kingston
    Kingston is a historic city in New York State known for being one of the state’s early capitals and a key cultural and economic center in the Hudson Valley region.
  • D. Kingston
    Kingston is a small city in eastern Tennessee that serves as the county seat of Roane County and lies within the greater Knoxville metropolitan area.
  • E. Kingston
    Kingston is a small unincorporated community and historic mining town located in central Nevada, United States.
  • 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_69a494267b4c819088c97a59182bf56a completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd0d5c288190b597dae0fbe3b43b completed March 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8311ba6481908aaca4c1e9d8b78f completed March 7, 2026, 7:57 p.m.
Created at: March 1, 2026, 7:45 p.m.