Triple

T19839799
Position Surface form Disambiguated ID Type / Status
Subject Punta Arenas campus E476695 entity
Predicate locatedInCity P40 FINISHED
Object Punta Arenas NE NERFINISHED

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: Punta Arenas | Statement: [Punta Arenas campus, locatedInCity, Punta Arenas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Punta Arenas
Context triple: [Punta Arenas campus, locatedInCity, Punta Arenas]
  • A. Punta Arenas, Chile chosen
    Punta Arenas, Chile is a major southern Chilean port city on the Strait of Magellan, known as a gateway to Patagonia and Antarctica.
  • B. Puerto Natales
    Puerto Natales is a small Patagonian port town in southern Chile, best known as the main gateway to Torres del Paine National Park.
  • C. La Serena
    La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
  • D. La Serena
    La Serena is a comarca in the Province of Badajoz in Extremadura, Spain, known for its rural landscapes, sheep farming, and production of La Serena cheese.
  • E. Valparaíso
    Valparaíso is a rural municipality located in the Caquetá Department of southern Colombia, known for its Amazonian landscapes and agricultural economy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65804be608190b49e110c3bf381bc completed April 20, 2026, 4:44 p.m.
Created at: April 10, 2026, 1:50 p.m.