Triple

T2808299
Position Surface form Disambiguated ID Type / Status
Subject Hutterites E54105 entity
Predicate significantPresenceIn P11111 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: [Hutterites, significantPresenceIn, Manitoba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manitoba
Context triple: [Hutterites, significantPresenceIn, 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. Ontario
    Ontario is Canada’s most populous province, home to the nation’s capital Ottawa and its largest city Toronto, and a major economic and cultural 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde2fdcf88190a52e515c166ea8f7 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69b28dc130a48190a4bf2259c206cf88 completed March 12, 2026, 9:56 a.m.
Created at: March 6, 2026, 9:59 p.m.