Triple

T5519167
Position Surface form Disambiguated ID Type / Status
Subject Limay River E144761 entity
Predicate flowsNear P350 FINISHED
Object Cipolletti E138479 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: Cipolletti | Statement: [Limay River, flowsNear, Cipolletti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cipolletti
Context triple: [Limay River, flowsNear, Cipolletti]
  • A. Cipolletti chosen
    Cipolletti is a city in Argentina’s Patagonia region, known as an important agricultural and service center in the Alto Valle of the Río Negro.
  • B. Chilecito
    Chilecito is a city in northwestern Argentina known for its wine production, mining history, and scenic Andean surroundings.
  • C. Melipeuco
    Melipeuco is a small Andean foothill town and commune in southern Chile known for its proximity to Conguillío National Park and the Llaima volcano.
  • D. Río Bueno
    Río Bueno is a Chilean city known for its agricultural surroundings and location along the Bueno River in the Los Ríos Region.
  • E. Caviahue
    Caviahue is a small Argentine town and ski resort in the Andes, known for its volcanic landscapes, thermal waters, and proximity to the Copahue volcano.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f6eb604819092e9b2207dc741a9 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11c9026fc8190abb0fb3e71d5639f completed March 23, 2026, 10:57 a.m.
Created at: March 22, 2026, 3:33 p.m.