Triple

T14963808
Position Surface form Disambiguated ID Type / Status
Subject Arauca River E373133 entity
Predicate hasFloodplain P14914 FINISHED
Object Llanos E58230 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: Llanos | Statement: [Arauca River, hasFloodplain, Llanos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llanos
Context triple: [Arauca River, hasFloodplain, 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 (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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6d0487c8190b7754af8c5014b37 completed April 15, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bdeec408190893d1db9254da24e completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 2:40 a.m.