Triple

T4750771
Position Surface form Disambiguated ID Type / Status
Subject Lost in Space (2018 TV series) E105470 entity
Predicate filmingLocation 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: [Lost in Space (2018 TV series), filmingLocation, British Columbia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: British Columbia
Context triple: [Lost in Space (2018 TV series), filmingLocation, 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. Yukon Territory
    Yukon Territory is a sparsely populated, mountainous territory in northwestern Canada known for its vast wilderness, subarctic climate, and rich Indigenous cultures.
  • D. Victoria Province
    Victoria Province was the colonial-era name for what is now Masvingo Province in southeastern Zimbabwe.
  • E. 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.
  • 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_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64c83af48190bd57be79c1505e9d completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be39ca8f6081909aecde545f211bb9 completed March 21, 2026, 6:25 a.m.
Created at: March 20, 2026, 1:20 p.m.