Triple

T10470554
Position Surface form Disambiguated ID Type / Status
Subject Die Another Day E246910 entity
Predicate setting P1957 FINISHED
Object Cuba E10524 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: Cuba | Statement: [Die Another Day, setting, Cuba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuba
Context triple: [Die Another Day, setting, Cuba]
  • A. Cuba chosen
    Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
  • B. Cuba
    Cuba is a municipality in Portugal’s Beja District, known for its rural Alentejo landscape and traditional wine production.
  • C. Dominican Republic
    The Dominican Republic is a Caribbean nation on the island of Hispaniola known for its beaches, mountainous interior, and vibrant blend of Spanish, African, and Taíno cultural influences.
  • D. Haiti
    Haiti is a Caribbean nation on the island of Hispaniola known for its rich Afro-Caribbean culture, history as the first independent Black republic, and frequent vulnerability to natural disasters.
  • E. Al-Hait
    Al-Hait is a town in northwestern Saudi Arabia located within the Ha'il Region, known for its traditional desert setting and regional agricultural activities.
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509305fec81908b1acd91ae1f875d completed April 7, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69d89ffdfd988190a37b3444d096e678 completed April 10, 2026, 7 a.m.
Created at: April 6, 2026, 12:20 p.m.