Triple

T2961421
Position Surface form Disambiguated ID Type / Status
Subject University of Regina E80056 entity
Predicate city P40 FINISHED
Object Regina E54058 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: Regina | Statement: [University of Regina, city, Regina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regina
Context triple: [University of Regina, city, Regina]
  • A. Regina, Saskatchewan, Canada chosen
    Regina, Saskatchewan, Canada is the capital city of the province of Saskatchewan, known as a major cultural and economic center on the Canadian Prairies.
  • B. Red Deer
    Red Deer is a mid-sized Canadian city in central Alberta known as a regional hub for agriculture, industry, and commerce between Calgary and Edmonton.
  • C. The Royal City
    The Royal City is the nickname of Guelph, a planned city in Ontario, Canada, known for its historic architecture, strong sense of community, and consistently high quality-of-life rankings.
  • D. Saskatoon
    Saskatoon is a major Canadian city on the South Saskatchewan River known for its vibrant cultural scene, universities, and role as an economic hub for the surrounding agricultural and resource-rich region.
  • E. Moose Jaw
    Moose Jaw is a mid-sized city in southern Saskatchewan, Canada, known for its historic downtown, underground tunnels, and role as a regional service and transportation hub.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad995454448190834aa5d47a4ed5ac completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e229afc8190ae634dbfb3ac4313 completed March 11, 2026, 8:56 a.m.
Created at: March 8, 2026, 2:57 p.m.