Triple

T19743647
Position Surface form Disambiguated ID Type / Status
Subject Medellín River E474194 entity
Predicate flowsThrough P225 FINISHED
Object Sabaneta NE NERFINISHED

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: Sabaneta | Statement: [Medellín River, flowsThrough, Sabaneta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabaneta
Context triple: [Medellín River, flowsThrough, Sabaneta]
  • A. Sabaneta chosen
    Sabaneta is a small but densely populated municipality in the Medellín metropolitan area of Colombia’s Aburrá Valley, known for its rapid urban growth and residential character.
  • B. Sabaneta
    Sabaneta is a municipal district in the San Juan de la Maguana municipality of the Dominican Republic.
  • C. Llanera
    Llanera is a rural municipality in the province of Nueva Ecija in the Philippines, known primarily for its agricultural economy and rice farming.
  • D. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • E. Betancuria
    Betancuria is a historic inland town and former capital of the Canary Island of Fuerteventura, known for its traditional architecture and rural charm.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51940a0819087bd2996f98da668 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65162f0f88190b652fff01ee23090 completed April 20, 2026, 4:16 p.m.
Created at: April 10, 2026, 1:47 p.m.