Triple

T16495994
Position Surface form Disambiguated ID Type / Status
Subject 45562 Alberta E400685 entity
Predicate name P16 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: [45562 Alberta, name, Alberta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alberta
Context triple: [45562 Alberta, name, Alberta]
  • A. 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.
  • B. Alberta chosen
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • C. Saskatchewan
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • D. Manitoba
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • E. British Columbia
    British Columbia is a western Canadian province known for its Pacific coastline, mountainous landscapes, and major cities such as Vancouver and Victoria.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e332c1c8190888a042d0192233a completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00606a3d5c8190a145ca35ce458f7e completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:14 a.m.