Triple

T2659528
Position Surface form Disambiguated ID Type / Status
Subject Sultan Kudarat E54692 entity
Predicate hasMunicipality P847 FINISHED
Object Columbio
Columbio is a rural municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and multicultural indigenous communities.
 E289109 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: Columbio | Statement: [Sultan Kudarat, hasMunicipality, Columbio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Columbio
Context triple: [Sultan Kudarat, hasMunicipality, Columbio]
  • A. Lleras
    Lleras is a Spanish-language surname notably associated with prominent Colombian political figures such as former president Alberto Lleras Camargo.
  • B. Tocaima
    Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
  • C. Mosquera
    Mosquera is a municipality in the department of Cundinamarca, Colombia, located near Bogotá and known for its growing industrial and residential development.
  • D. Marmato
    Marmato is a historic Colombian mining town in the Caldas Department, renowned for its centuries-old gold extraction and terraced mountainside setting.
  • E. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • 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: Columbio
Triple: [Sultan Kudarat, hasMunicipality, Columbio]
Generated description
Columbio is a rural municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and multicultural indigenous communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Columbio
Target entity description: Columbio is a rural municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and multicultural indigenous communities.
  • A. Lleras
    Lleras is a Spanish-language surname notably associated with prominent Colombian political figures such as former president Alberto Lleras Camargo.
  • B. Tocaima
    Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
  • C. Mosquera
    Mosquera is a municipality in the department of Cundinamarca, Colombia, located near Bogotá and known for its growing industrial and residential development.
  • D. Marmato
    Marmato is a historic Colombian mining town in the Caldas Department, renowned for its centuries-old gold extraction and terraced mountainside setting.
  • E. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd94f3b1881909bd36cfe61c254a5 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa056f478819091f6751edfee0132 completed March 10, 2026, 4:38 a.m.
NEDg Description generation batch_69afa12b8d388190a50de5f41c0fa782 completed March 10, 2026, 4:42 a.m.
NED2 Entity disambiguation (via description) batch_69afa4e2f56c8190a418aef660da8e12 completed March 10, 2026, 4:58 a.m.
Created at: March 6, 2026, 9:53 p.m.