Triple

T3938803
Position Surface form Disambiguated ID Type / Status
Subject America/Regina E90981 entity
Predicate subdivision P747 FINISHED
Object Saskatchewan E15926 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: Saskatchewan | Statement: [America/Regina, subdivision, Saskatchewan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saskatchewan
Context triple: [America/Regina, subdivision, Saskatchewan]
  • A. Saskatchewan chosen
    Saskatchewan is a prairie and boreal province in western Canada known for its vast flat landscapes, agriculture, and significant natural resources.
  • B. Manitoba
    Manitoba is a central Canadian province known for its vast prairies, numerous lakes, and northern boreal forests.
  • C. Alberta
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • D. Prince Albert, Saskatchewan
    Prince Albert, Saskatchewan is a small city in central Saskatchewan, Canada, known as a regional service hub and gateway to nearby lakes, forests, and outdoor recreation areas.
  • E. Churchill, Manitoba
    Churchill, Manitoba is a remote northern Canadian town on the shores of Hudson Bay, best known as one of the world’s premier destinations for viewing polar bears and beluga whales.
  • 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_69aed95f26e0819094b0e71974543a19 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeedfb12b88190a6ca6574b1aadb6e completed March 9, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b595f59e908190a45b3b9c767974fb completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:24 p.m.