Triple

T2758683
Position Surface form Disambiguated ID Type / Status
Subject Gabo E61165 entity
Predicate refersToPersonResidence P22499 FINISHED
Object Bogotá, Colombia E1526 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: Bogotá, Colombia | Statement: [Gabo, refersToPersonResidence, Bogotá, Colombia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bogotá, Colombia
Context triple: [Gabo, refersToPersonResidence, Bogotá, Colombia]
  • A. Bogotá chosen
    Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
  • B. La Candelaria, Bogotá
    La Candelaria, Bogotá is the historic colonial center of Colombia’s capital city, known for its preserved architecture, cultural institutions, and vibrant political and academic life.
  • C. Sucre, Colombia
    Sucre, Colombia is a department on Colombia’s Caribbean coast known for its agricultural economy, coastal wetlands, and cultural traditions rooted in the broader Caribbean region.
  • D. Medellín
    Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
  • E. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • 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_69ab4b7a85bc819094a349b84beb1f2c completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd2121548190b96f174e6f61f9b5 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1f852ebbc8190885b819a79719c6d completed March 11, 2026, 11:18 p.m.
Created at: March 6, 2026, 9:57 p.m.