Triple

T8308410
Position Surface form Disambiguated ID Type / Status
Subject Sucre, Colombia E194522 entity
Predicate hasMunicipality P847 FINISHED
Object Coveñas E567777 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: Coveñas | Statement: [Sucre, Colombia, hasMunicipality, Coveñas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coveñas
Context triple: [Sucre, Colombia, hasMunicipality, Coveñas]
  • A. Coveñas chosen
    Coveñas is a coastal municipality and popular beach destination on Colombia’s Caribbean Sea, known for its tourism and oil-related port activities.
  • B. Churriana
    Churriana is a district of Málaga in southern Spain, known for encompassing the area around Málaga–Costa del Sol Airport and lying close to the Mediterranean coast.
  • C. Cardeñosa
    Cardeñosa is a small municipality in the province of Ávila, in the autonomous community of Castile and León, Spain.
  • D. Osuna
    Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
  • E. Cosío
    Cosío is a small municipality and town located in the northern part of the Mexican state of Aguascalientes.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2c06608190bd21633af07a530b completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde772559c819080f411802bbcfef1 completed April 2, 2026, 3:50 a.m.
Created at: March 30, 2026, 5:54 p.m.