Triple

T216118
Position Surface form Disambiguated ID Type / Status
Subject Last Chance to See E4108 entity
Predicate setting P1957 FINISHED
Object Zaire E9695 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: Zaire | Statement: [Last Chance to See, setting, Zaire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zaire
Context triple: [Last Chance to See, setting, Zaire]
  • A. Democratic Republic of the Congo chosen
    The Democratic Republic of the Congo is a vast, resource-rich Central African nation known for the Congo River basin, extensive rainforests, and a history marked by colonial exploitation and ongoing political instability.
  • B. Republic of the Congo
    The Republic of the Congo is a Central African nation along the Atlantic coast, known for its vast tropical rainforests, rich biodiversity, and significant oil and mineral resources.
  • C. Zambia
    Zambia is a landlocked country in south-central Africa known for the Victoria Falls on the Zambezi River, diverse wildlife, and copper-rich economy.
  • D. Congo
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • E. Angola
    Angola is a resource-rich country on Africa’s southwest coast, known for its oil and diamond industries and its history of a long civil war following independence.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c4edfa081909fe97c86c3c7801d completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a43e6744888190b4514f057fc98498 completed March 1, 2026, 1:25 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.