Triple

T408792
Position Surface form Disambiguated ID Type / Status
Subject Tlingit E9440 entity
Predicate region P40 FINISHED
Object British Columbia E11524 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: British Columbia | Statement: [Tlingit, region, British Columbia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: British Columbia
Context triple: [Tlingit, region, British Columbia]
  • A. British Columbia chosen
    British Columbia is a western Canadian province known for its Pacific coastline, mountainous landscapes, and major cities such as Vancouver and Victoria.
  • B. Alberta
    Alberta is a western Canadian province known for its vast prairies, Rocky Mountains, and significant natural resource industries.
  • C. Ontario
    Ontario is Canada’s most populous province, home to the nation’s capital Ottawa and its largest city Toronto, and a major economic and cultural hub.
  • D. Ontario
    Ontario is a city in southwestern San Bernardino County, California, known as a major logistics and transportation hub anchored by Ontario International Airport and extensive freeway and rail connections.
  • 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 (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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecbf0650819080753815ca280eec completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a47469d5248190a14f44d53a3e6e8f completed March 1, 2026, 5:16 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.