Triple

T19297738
Position Surface form Disambiguated ID Type / Status
Subject Laguna Blanca National Park E482610 entity
Predicate ecosystemType P952 FINISHED
Object Patagonian steppe 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: Patagonian steppe | Statement: [Laguna Blanca National Park, ecosystemType, Patagonian steppe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patagonian steppe
Context triple: [Laguna Blanca National Park, ecosystemType, Patagonian steppe]
  • A. Patagonian steppe chosen
    The Patagonian steppe is a vast, windswept cold desert and grassland region in southern Argentina, characterized by sparse vegetation, arid climate, and extensive sheep ranching.
  • B. Pampas
    Pampas is a town in central Peru that serves as the administrative and commercial hub of Tayacaja Province in the Huancavelica Region.
  • C. Pampas
    The Pampas is a vast fertile lowland plain in South America, primarily in Argentina, known for its grasslands, agriculture, and cattle ranching.
  • D. Pampa
    Pampa is a small city in the Texas Panhandle known historically for its role in the oil and gas industry and as a regional service and trade center.
  • E. Pampa
    Pampa was a pioneering 10th-century Kannada poet, celebrated as one of the “three gems” of classical Kannada literature and best known for his epic works like the Adipurana and Vikramarjuna Vijaya.
  • 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_69d8e8cf61b0819096fe3e4107827c4e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fc86f8648190920d122bb141c6e5 completed April 20, 2026, 10:14 a.m.
Created at: April 10, 2026, 1:31 p.m.