Triple

T4729116
Position Surface form Disambiguated ID Type / Status
Subject Quillota E104958 entity
Predicate nearbyCity P350 FINISHED
Object La Calera E388864 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: [Quillota, nearbyCity, La Calera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Calera
Context triple: [Quillota, nearbyCity, La Calera]
  • A. La Calera
    La Calera is a Colombian town and municipality in the Andean department of Cundinamarca, known for its mountainous landscapes and proximity to Bogotá.
  • B. La Calera chosen
    La Calera is a Chilean city and municipality in the Valparaíso Region known for its cement industry and role as a commercial and transport hub in the interior of the region.
  • C. 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.
  • D. San Nicolás
    San Nicolás is a central Buenos Aires neighborhood known as a major commercial and cultural hub that includes landmarks like the Obelisco and the city’s main theater district.
  • E. Pateros
    Pateros is the smallest and only landlocked municipality in Metro Manila, Philippines, known for its duck-raising industry and production of balut.
  • 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_69bd43ed84648190ae0b7ee8e8d00482 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd646135c881909030c21a163cc619 completed March 20, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a0739a88190aefc952d9d9b39e2 completed March 21, 2026, 6:26 a.m.
Created at: March 20, 2026, 1:19 p.m.