Triple

T1916219
Position Surface form Disambiguated ID Type / Status
Subject Sopó E40022 entity
Predicate borderedBy P224 FINISHED
Object La Calera E40577 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: La Calera | Statement: [Sopó, borderedBy, La Calera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Calera
Context triple: [Sopó, borderedBy, La Calera]
  • A. La Calera chosen
    La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
  • B. San José de Maipo
    San José de Maipo is a mountainous commune and town in central Chile known as a gateway to the Cajón del Maipo canyon and the Andes for outdoor and ecotourism activities.
  • C. Pateros
    Pateros is the smallest and only landlocked municipality in Metro Manila, Philippines, known for its duck-raising industry and production of balut.
  • D. La Serena
    La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
  • E. Junín
    Junín is a central highland region of Peru known for its Andean landscapes, rich mining and agricultural activities, and historical role in Peru’s independence.
  • 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_69a8864298748190a2f2fd34f7ef8d77 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb20f54848190b9457e1231aa49db completed March 7, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3da81308190a49844a8ac2997da completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.