Triple

T5288832
Position Surface form Disambiguated ID Type / Status
Subject Meyer Lansky E119689 entity
Predicate isAssociatedWithPlace P3158 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: [Meyer Lansky, isAssociatedWithPlace, Cuba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cuba
Context triple: [Meyer Lansky, isAssociatedWithPlace, 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. Grenada
    Grenada is a small Caribbean island nation known for its spice production, picturesque beaches, and lush mountainous interior.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84db300c8190a63ac51552f0e9a6 completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06b04cd881909e31b4e533dc4ae8 completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:52 p.m.