Triple

T9300444
Position Surface form Disambiguated ID Type / Status
Subject Horcones Valley E223744 entity
Predicate hasNearbyCity P350 FINISHED
Object Mendoza E251243 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: Mendoza | Statement: [Horcones Valley, hasNearbyCity, Mendoza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mendoza
Context triple: [Horcones Valley, hasNearbyCity, Mendoza]
  • A. Mendoza chosen
    Mendoza is a major city in western Argentina known as a gateway to the Andes and the country’s premier wine-producing region.
  • B. Mendoza
    Mendoza is a common Spanish-language surname borne by numerous notable individuals across the Spanish-speaking world.
  • C. 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.
  • D. 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.
  • E. Cafayate
    Cafayate is a renowned town in northwestern Argentina famous for its high-altitude vineyards, particularly Torrontés wine, and striking desert-and-mountain landscapes.
  • 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_69ca8423edb08190bc0c91287a484768 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd08d070c881908bed41aada6f85ae completed April 1, 2026, noon
NED1 Entity disambiguation (via context triple) batch_69d12cc59610819090adf2b4c3f5cec3 completed April 4, 2026, 3:22 p.m.
Created at: March 30, 2026, 7:36 p.m.