Triple

T7235595
Position Surface form Disambiguated ID Type / Status
Subject Bannatyne campus E155216 entity
Predicate locatedIn P40 FINISHED
Object Manitoba E15186 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: Manitoba | Statement: [Bannatyne campus, locatedIn, Manitoba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manitoba
Context triple: [Bannatyne campus, locatedIn, Manitoba]
  • A. Manitoba chosen
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • B. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • C. Alberta
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • D. Emerson, Manitoba
    Emerson, Manitoba is a small Canadian border town in southern Manitoba situated along the Red River near the U.S. state of North Dakota.
  • E. Great Plains Province
    The Great Plains Province is a vast, mostly flat to gently rolling region of central North America characterized by grasslands, prairies, and extensive agricultural use.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea33dd3481908ebb050e1fab5aaa completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc32d6c48190ae78b3d1227bb868 completed March 28, 2026, 12:40 p.m.
Created at: March 27, 2026, 2:55 p.m.