Triple

T9680536
Position Surface form Disambiguated ID Type / Status
Subject Division No. 3, Alberta E234266 entity
Predicate partOf P40 FINISHED
Object Province of 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: Province of Alberta | Statement: [Division No. 3, Alberta, partOf, Province of Alberta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Province of Alberta
Context triple: [Division No. 3, Alberta, partOf, Province of 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. Great Plains Province
    The Great Plains Province is a vast, mostly flat to gently rolling region of central North America characterized by grasslands, prairies, and extensive agricultural use.
  • D. Mountain Province
    Mountain Province is a landlocked, mountainous province in the northern Philippines known for its rugged terrain, indigenous cultures, and rice terraces.
  • 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 (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_69ca84c99e34819092e5563a7106cfca completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9c9dcbe881908ae926a5b5eae759 completed April 1, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c40329448190bccac60a20dcb9d1 completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:16 p.m.