Triple

T18517462
Position Surface form Disambiguated ID Type / Status
Subject Casanare campaign E452501 entity
Predicate location P40 FINISHED
Object Llanos 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: Llanos | Statement: [Casanare campaign, location, Llanos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llanos
Context triple: [Casanare campaign, location, Llanos]
  • A. Los Llanos
    Los Llanos is a vast tropical grassland plain in northern South America, known for its cattle ranching, rich wildlife, and seasonal flooding.
  • B. Llanos de Moxos
    Llanos de Moxos is a vast seasonally flooded tropical savanna and wetland region in northern Bolivia, known for its rich biodiversity and extensive pre-Columbian earthworks.
  • C. Orinoco Llanos floodplains chosen
    The Orinoco Llanos floodplains are vast seasonally inundated grasslands in the Orinoco River basin of Venezuela and Colombia, known for their rich biodiversity and extensive wetlands.
  • D. La Sabana
    La Sabana is a locality within the coastal region of Acapulco in the Mexican state of Guerrero, known as part of the broader urban and suburban area surrounding the resort city.
  • E. Cuban plains
    The Cuban plains are broad, low-lying fertile regions of Cuba characterized by extensive agriculture and relatively flat terrain.
  • 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_69d8d386df84819092355ebb260d848e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5338b2cd0819095db59f6bfc70814 completed April 19, 2026, 7:56 p.m.
Created at: April 10, 2026, 11:36 a.m.