Triple

T7822937
Position Surface form Disambiguated ID Type / Status
Subject Granma Province E181175 entity
Predicate hasMunicipality P847 FINISHED
Object Niquero E682079 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: Niquero | Statement: [Granma Province, hasMunicipality, Niquero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niquero
Context triple: [Granma Province, hasMunicipality, Niquero]
  • A. Niquero chosen
    Niquero is a coastal town and municipality in Granma Province, Cuba, known for its historical role in the Cuban Revolution and proximity to important coastal and natural areas.
  • B. Porvenir
    Porvenir is a small town that serves as the capital of Pando Department in northern Bolivia, near the border with Brazil.
  • C. Porvenir
    Porvenir is a small Chilean town on Tierra del Fuego that serves as an important fishing and service port on the Strait of Magellan.
  • D. Aculco
    Aculco is a Mexico City Metro station located in the eastern part of the city, serving local commuters on Line 8.
  • E. Carso
    Carso is a limestone plateau region in northeastern Italy and southwestern Slovenia, known for its distinctive karst landscapes, caves, and sinkholes.
  • 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_69ca8282ccec819083c48efb72d21cf9 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cafa095d7081908b3e492ce58b5d5f completed March 30, 2026, 10:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb5a66c1c0819087ce9890f28bb022 completed March 31, 2026, 5:23 a.m.
Created at: March 30, 2026, 4:42 p.m.