Triple

T13577586
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Engineering and Applied Science, University of Regina E324327 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: [Faculty of Engineering and Applied Science, University of Regina, city, Regina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Regina
Context triple: [Faculty of Engineering and Applied Science, University of Regina, city, Regina]
  • A. Regina
    Regina is a 1949 opera by American composer Marc Blitzstein, adapted from Lillian Hellman’s play "The Little Foxes."
  • B. Regina
    Regina is the given first name of American actress Jenna Fischer, best known for her role as Pam Beesly on the U.S. version of "The Office."
  • C. Regina
    Regina is a feminine given name of Latin origin meaning "queen," used in various cultures and languages.
  • D. Regina
    Regina is a fictional character known for her role as a maid.
  • E. 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.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb02de1988190af2d473973ecd529 completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bbbe3c08190a359dfe7c3c8f15c completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:48 p.m.