Triple

T8528635
Position Surface form Disambiguated ID Type / Status
Subject Cesar Department E201884 entity
Predicate capital P234 FINISHED
Object Valledupar E518422 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: Valledupar | Statement: [Cesar Department, capital, Valledupar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valledupar
Context triple: [Cesar Department, capital, Valledupar]
  • A. Valledupar chosen
    Valledupar is a major city in northern Colombia known as the cradle of vallenato music and for its rich cultural traditions.
  • B. Cartagena del Chairá
    Cartagena del Chairá is a rural municipality in southern Colombia’s Caquetá Department, known for its Amazonian rainforest environment and history of armed conflict presence.
  • C. Cúcuta
    Cúcuta is a major Colombian city on the border with Venezuela, known as an important commercial and transportation hub in the northeast of the country.
  • D. Barranquilla
    Barranquilla is a major port city on Colombia’s Caribbean coast, known for its vibrant culture and famous Carnival festival.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe672e0588190a84328e1bf974f08 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf27fc84cc81909b788839bbc8e016 completed April 3, 2026, 2:37 a.m.
Created at: March 30, 2026, 6:17 p.m.