Triple

T20620626
Position Surface form Disambiguated ID Type / Status
Subject Flicka E506687 entity
Predicate filmingLocation P40 FINISHED
Object Alberta, Canada 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, Canada | Statement: [Flicka, filmingLocation, Alberta, Canada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberta, Canada
Context triple: [Flicka, filmingLocation, Alberta, Canada]
  • 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. Athabasca, Alberta
    Athabasca, Alberta is a small town in northern Alberta, Canada, known historically as a transportation and trading hub and for its location along the Athabasca River.
  • E. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6abe19ca481908c896bec49a025cd completed April 20, 2026, 10:42 p.m.
Created at: April 16, 2026, 11:42 a.m.