Triple

T7058897
Position Surface form Disambiguated ID Type / Status
Subject Cathedral of Our Lady of the Assumption E164164 entity
Predicate country P26 FINISHED
Object Haiti E4291 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: Haiti | Statement: [Cathedral of Our Lady of the Assumption, country, Haiti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haiti
Context triple: [Cathedral of Our Lady of the Assumption, country, Haiti]
  • A. Haiti chosen
    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.
  • B. 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.
  • C. Arcahaie, Haiti
    Arcahaie is a coastal commune in western Haiti historically recognized as the birthplace of the Haitian national flag.
  • D. Grenada
    Grenada is a small Caribbean island nation known for its spice production, picturesque beaches, and lush mountainous interior.
  • 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_69c68861678881909961ddf4d779f750 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e26b2acc8190b212ec77b74c419f completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7882712548190a0c7e5660c61625d completed March 28, 2026, 7:49 a.m.
Created at: March 27, 2026, 2:38 p.m.