Triple

T4204613
Position Surface form Disambiguated ID Type / Status
Subject Buenos Aires Province E86153 entity
Predicate locatedInRegion P40 FINISHED
Object Humid Pampas E25063 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: Humid Pampas | Statement: [Buenos Aires Province, locatedInRegion, Humid Pampas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Humid Pampas
Context triple: [Buenos Aires Province, locatedInRegion, Humid Pampas]
  • A. Pampas chosen
    The Pampas is a vast fertile lowland plain in South America, primarily in Argentina, known for its grasslands, agriculture, and cattle ranching.
  • B. Patagonian steppe
    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.
  • C. 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.
  • D. 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.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0382eafc8190946bf45bf28095dd completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b596258db88190aed602eeb2323fee completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:49 p.m.