Triple

T12972980
Position Surface form Disambiguated ID Type / Status
Subject Nakiska Ski Resort E321448 entity
Predicate province P604 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: [Nakiska Ski Resort, province, Alberta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberta
Context triple: [Nakiska Ski Resort, province, 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. Yukon Territory
    Yukon Territory is a sparsely populated, mountainous territory in northwestern Canada known for its vast wilderness, subarctic climate, and rich Indigenous cultures.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e4322c08190abd43daadf16097f completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc0b8188190a6a40bb4edf53e25 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 8:36 p.m.