Triple

T14794839
Position Surface form Disambiguated ID Type / Status
Subject Caldas E347746 entity
Predicate hasMunicipality P847 FINISHED
Object Supía E188428 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: Supía | Statement: [Caldas, hasMunicipality, Supía]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Supía
Context triple: [Caldas, hasMunicipality, Supía]
  • A. Supía chosen
    Supía is a municipality in the Caldas Department of Colombia, known historically for gold mining and its indigenous Emberá Chamí heritage.
  • B. Ascurra
    Ascurra is a small municipality in the state of Santa Catarina in southern Brazil, known for its Italian immigrant heritage and location in the Vale do Itajaí region.
  • C. Sicuani
    Sicuani is a highland city in southern Peru that serves as an important commercial and transport hub in the Cusco region.
  • D. Huambisa
    Huambisa is an indigenous Jivaroan language spoken by the Huambisa people of the northern Peruvian Amazon.
  • E. Cochamó
    Cochamó is a rural commune and village in Chile’s Los Lagos Region, known for its dramatic granite valleys, lush temperate rainforests, and outdoor recreation such as trekking and rock climbing.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5fdd548190a2ee5e668c2b20b4 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64f349fc8190b049542fef963b58 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:31 a.m.