Triple

T13983211
Position Surface form Disambiguated ID Type / Status
Subject A Wedding in Haiti E336366 entity
Predicate mainSubject P3 FINISHED
Object Dominican Republic E18248 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: Dominican Republic | Statement: [A Wedding in Haiti, mainSubject, Dominican Republic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dominican Republic
Context triple: [A Wedding in Haiti, mainSubject, Dominican Republic]
  • A. Dominican Republic chosen
    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.
  • B. Cuba
    Cuba is a Caribbean island nation known for its communist government, historic Havana architecture, classic cars, and influential music and culture.
  • C. Cuba
    Cuba is a municipality in Portugal’s Beja District, known for its rural Alentejo landscape and traditional wine production.
  • 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. Dominica
    Dominica is a small island nation in the Caribbean known for its lush rainforests, volcanic landscapes, and rich biodiversity.
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea2e8808190a1203a6386224bd8 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0934b74819094ec7309c23a3e2a completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:18 p.m.