Triple

T15366266
Position Surface form Disambiguated ID Type / Status
Subject Apure State E367421 entity
Predicate knownFor P22 FINISHED
Object Llanos plains E1127984 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 plains | Statement: [Apure State, knownFor, Llanos plains]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Llanos plains
Context triple: [Apure State, knownFor, Llanos plains]
  • A. Orinoco Llanos floodplains
    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.
  • B. Los Llanos chosen
    Los Llanos is a vast tropical grassland plain in northern South America, known for its cattle ranching, rich wildlife, and seasonal flooding.
  • C. 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.
  • D. Cuban plains
    The Cuban plains are broad, low-lying fertile regions of Cuba characterized by extensive agriculture and relatively flat terrain.
  • E. Isabela plains
    Isabela plains is a broad, fertile lowland area in the Philippine province of Isabela, known as one of the country’s major agricultural regions.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e497de48190be249b110999ec5c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cec4f2481908fae5209bfd48dcf completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:18 a.m.