Triple

T20095146
Position Surface form Disambiguated ID Type / Status
Subject Fort McMurray E496379 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Alberta NE NERFINISHED

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: [Fort McMurray, locatedInAdministrativeTerritorialEntity, Alberta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberta
Context triple: [Fort McMurray, locatedInAdministrativeTerritorialEntity, Alberta]
  • A. Alberta chosen
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • B. Alberta
    Alberta is a character in August Wilson’s play "Fences," known as the woman with whom Troy Maxson has an extramarital affair, symbolizing his desires and the fractures in his family life.
  • C. Alberta
    "Alberta" is a song featured on the album "Southbound."
  • D. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • E. Manitoba
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6666b891c8190b4e4a60b73728771 completed April 20, 2026, 5:46 p.m.
Created at: April 11, 2026, 11:24 p.m.