Triple

T12333985
Position Surface form Disambiguated ID Type / Status
Subject San Juan de la Maguana E294033 entity
Predicate hasMunicipalDistrict P78738 FINISHED
Object Sabaneta
Sabaneta is a municipal district in the San Juan de la Maguana municipality of the Dominican Republic.
E980163 NE FINISHED

How this triple was built (4 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: [San Juan de la Maguana, hasMunicipalDistrict, Sabaneta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabaneta
Context triple: [San Juan de la Maguana, hasMunicipalDistrict, Sabaneta]
  • A. Sabaneta
    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. Llanera
    Llanera is a rural municipality in the province of Nueva Ecija in the Philippines, known primarily for its agricultural economy and rice farming.
  • C. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • D. Betancuria
    Betancuria is a historic inland town and former capital of the Canary Island of Fuerteventura, known for its traditional architecture and rural charm.
  • E. Sibaté
    Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sabaneta
Triple: [San Juan de la Maguana, hasMunicipalDistrict, Sabaneta]
Generated description
Sabaneta is a municipal district in the San Juan de la Maguana municipality of the Dominican Republic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sabaneta
Target entity description: Sabaneta is a municipal district in the San Juan de la Maguana municipality of the Dominican Republic.
  • A. Sabaneta
    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. Llanera
    Llanera is a rural municipality in the province of Nueva Ecija in the Philippines, known primarily for its agricultural economy and rice farming.
  • C. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • D. Betancuria
    Betancuria is a historic inland town and former capital of the Canary Island of Fuerteventura, known for its traditional architecture and rural charm.
  • E. Sibaté
    Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
  • F. None of above. chosen

Provenance (5 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f64ad20819080d99e57833b4b51 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6346c06208190b4e39fcbdb6a06fa completed May 2, 2026, 5:29 p.m.
NEDg Description generation batch_69f6356b545c819089a5f5b901afc5f2 completed May 2, 2026, 5:33 p.m.
NED2 Entity disambiguation (via description) batch_69f636382ffc8190becfae41757a45d8 completed May 2, 2026, 5:36 p.m.
Created at: April 8, 2026, 9:53 p.m.