Triple

T1582569
Position Surface form Disambiguated ID Type / Status
Subject Departamento de Cundinamarca E33998 entity
Predicate hasMajorCity P316 FINISHED
Object Zipaquirá E33041 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: Zipaquirá | Statement: [Departamento de Cundinamarca, hasMajorCity, Zipaquirá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zipaquirá
Context triple: [Departamento de Cundinamarca, hasMajorCity, Zipaquirá]
  • A. Zipaquirá chosen
    Zipaquirá is a historic Colombian city famed for its underground Salt Cathedral and colonial architecture, located north of Bogotá.
  • B. Yucay
    Yucay is a small Andean town in Peru’s Sacred Valley, known for its traditional agriculture, Inca terraces, and scenic mountain surroundings.
  • C. Chocontá
    Chocontá is a municipality and town in central Colombia known for its agricultural production and colonial-era history.
  • D. Colina
    Colina is a commune and city in central Chile known for its growing residential areas and proximity to Santiago in the Santiago Metropolitan Region.
  • E. Huacho
    Huacho is a coastal city in central Peru that serves as an important commercial and agricultural hub north of Lima.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908ef80a48190bd5a8e51c65e5588 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51b2b4d4819093f2ae3759838757 completed March 8, 2026, 10:38 a.m.
Created at: March 4, 2026, 7:27 p.m.