Triple

T10377146
Position Surface form Disambiguated ID Type / Status
Subject Iglesia Católica de Porvenir E244535 entity
Predicate locatedIn P40 FINISHED
Object Porvenir unclear NED1 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: Porvenir | Statement: [Iglesia Católica de Porvenir, locatedIn, Porvenir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porvenir
Context triple: [Iglesia Católica de Porvenir, locatedIn, Porvenir]
  • A. 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.
  • B. Porvenir
    Porvenir is a small town that serves as the capital of Pando Department in northern Bolivia, near the border with Brazil.
  • C. Niquero
    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.
  • D. Prestea
    Prestea is a mining town in southwestern Ghana known for its significant gold deposits and long history of gold extraction.
  • E. Pacasmayo
    Pacasmayo is a coastal city in northern Peru known for its long pier, surfing beaches, and colonial-era architecture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e98f312481909f7276fc3762d7bc completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e6f30c88190992242b6e0c43581 completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:02 p.m.