Triple

T455655
Position Surface form Disambiguated ID Type / Status
Subject Dirty Thirties E7226 entity
Predicate affectedArea P1586 FINISHED
Object Alberta E16102 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: Alberta | Statement: [Dirty Thirties, affectedArea, Alberta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberta
Context triple: [Dirty Thirties, affectedArea, Alberta]
  • A. Alberta chosen
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • B. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • C. Manitoba
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • D. British Columbia
    British Columbia is a western Canadian province known for its Pacific coastline, mountainous landscapes, and major cities such as Vancouver and Victoria.
  • E. Northwest Territories
    The Northwest Territories is a vast, sparsely populated federal territory in northern Canada known for its subarctic and Arctic landscapes, Indigenous cultures, and natural resources.
  • 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_69a2e7e5c5bc8190a1dc8178218fba40 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ef9f772c8190863399c5ee1378fe completed Feb. 28, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b8a96a188190b7a6be463de3d736 completed March 1, 2026, 10:07 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.