Triple

T6623584
Position Surface form Disambiguated ID Type / Status
Subject Neuquén River E149737 entity
Predicate majorCityOnRiver P316 FINISHED
Object Neuquén E110806 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: Neuquén | Statement: [Neuquén River, majorCityOnRiver, Neuquén]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neuquén
Context triple: [Neuquén River, majorCityOnRiver, Neuquén]
  • A. Santiago del Estero
    Santiago del Estero is a historic city in northern Argentina that serves as the capital of Santiago del Estero Province and is considered one of the country’s oldest continuously inhabited settlements.
  • B. Neuquén Province chosen
    Neuquén Province is a region in western Argentina known for its Andean landscapes, oil and gas production, and popular Patagonian tourist destinations.
  • C. Mendoza
    Mendoza is a common Spanish-language surname borne by numerous notable individuals across the Spanish-speaking world.
  • D. Mendoza
    Mendoza is a major city in western Argentina known as a gateway to the Andes and the country’s premier wine-producing region.
  • E. Mendoza Province
    Mendoza Province is a region in western Argentina known for its Andean landscapes, including the towering Aconcagua peak, and its prominent wine-producing industry.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af7decb08190a7b1ddb95e534a6a completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c86822add88190909a82b9c263bb6f completed March 28, 2026, 11:45 p.m.
Created at: March 27, 2026, 1:58 p.m.