Triple

T6330946
Position Surface form Disambiguated ID Type / Status
Subject Copiapó Province E142378 entity
Predicate capital P234 FINISHED
Object Copiapó E34766 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: Copiapó | Statement: [Copiapó Province, capital, Copiapó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copiapó
Context triple: [Copiapó Province, capital, Copiapó]
  • A. Copiapó chosen
    Copiapó is a city in northern Chile known as a regional mining center and gateway to the Atacama Desert.
  • B. Chiguayante
    Chiguayante is a Chilean city located near Concepción, known as part of the Greater Concepción metropolitan area in the south-central part of the country.
  • C. Cucunubá
    Cucunubá is a small colonial-era town in the Cundinamarca department of Colombia, known for its traditional wool textiles and scenic Andean highland landscapes.
  • D. Zapatoca
    Zapatoca is a historic town and municipality in northeastern Colombia known for its colonial architecture, mild climate, and scenic Andean landscapes.
  • E. Chapala
    Chapala is a lakeside town in the Mexican state of Jalisco, known for its location on the shores of Lake Chapala, the country’s largest freshwater lake.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06514cbe8819096dbeb17ccb3e3d5 completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6041aac948190ad7dd4d5683903ed completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.