Triple

T8309715
Position Surface form Disambiguated ID Type / Status
Subject Sumapaz Province E194559 entity
Predicate contains P35 FINISHED
Object Arbeláez
Arbeláez is a municipality in the Cundinamarca Department of Colombia, known for its mountainous landscapes and agricultural activities.
E734715 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: Arbeláez | Statement: [Sumapaz Province, contains, Arbeláez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arbeláez
Context triple: [Sumapaz Province, contains, Arbeláez]
  • A. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • B. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • C. Carballal
    Carballal is a Spanish surname, likely of Galician origin, that serves as a variant of the more common surname Carvajal.
  • D. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • E. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • 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: Arbeláez
Triple: [Sumapaz Province, contains, Arbeláez]
Generated description
Arbeláez is a municipality in the Cundinamarca Department of Colombia, known for its mountainous landscapes and agricultural activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arbeláez
Target entity description: Arbeláez is a municipality in the Cundinamarca Department of Colombia, known for its mountainous landscapes and agricultural activities.
  • A. Zorreguieta
    Zorreguieta is an Argentine family name best known as the maiden surname of Queen Máxima of the Netherlands.
  • B. Echeandía
    Echeandía is a small town in central Ecuador known for its agricultural activities and rural Andean setting.
  • C. Carballal
    Carballal is a Spanish surname, likely of Galician origin, that serves as a variant of the more common surname Carvajal.
  • D. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • E. Rojas
    Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2d2c30819095075940479b75a7 completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1ce5a0c881909ee517678cdc4ef2 completed April 2, 2026, 7:38 a.m.
NEDg Description generation batch_69ce1ebf0f808190846f70438f45afbf completed April 2, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_69ce1f68aa04819081538dda256f4169 completed April 2, 2026, 7:48 a.m.
Created at: March 30, 2026, 5:54 p.m.