Triple

T830243
Position Surface form Disambiguated ID Type / Status
Subject Malbec E17947 entity
Predicate notableRegion P22 FINISHED
Object Mendoza E50047 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: [Malbec, notableRegion, Mendoza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mendoza
Context triple: [Malbec, notableRegion, Mendoza]
  • A. Mendoza Province chosen
    Mendoza Province is a region in western Argentina known for its Andean landscapes, including the towering Aconcagua peak, and its prominent wine-producing industry.
  • B. Santa Fe, Argentina
    Santa Fe, Argentina is a major river port city and the capital of Santa Fe Province, located in northeastern Argentina along the Paraná and Salado rivers.
  • C. Bariloche
    Bariloche is a popular Argentine city in the Andean region known for its lakes, mountains, skiing, and Swiss-style alpine architecture.
  • D. Catamarca Province
    Catamarca Province is a sparsely populated, mountainous province in northwestern Argentina known for its high Andean peaks, arid landscapes, and rich mining and colonial history.
  • E. Buenos Aires Province
    Buenos Aires Province is Argentina’s largest and most populous province, surrounding but not including the federal capital and encompassing major agricultural, industrial, and coastal 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_69a4937c9c188190aaa216f6b466f452 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abb384988190949d2df65662f76d completed March 1, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b84547508190b82c2012f4342529 completed March 4, 2026, 4:42 a.m.
Created at: March 1, 2026, 7:38 p.m.