Triple

T7061669
Position Surface form Disambiguated ID Type / Status
Subject Canadian Northern Railway E164230 entity
Predicate hasRouteThrough P4374 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: [Canadian Northern Railway, hasRouteThrough, Manitoba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manitoba
Context triple: [Canadian Northern Railway, hasRouteThrough, 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_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e45b7488819094d2dd337731dab9 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c788b4b6788190aa4e74b9e7eb7eaa completed March 28, 2026, 7:52 a.m.
Created at: March 27, 2026, 2:38 p.m.