Triple

T851653
Position Surface form Disambiguated ID Type / Status
Subject Biobío Region E18398 entity
Predicate hasIndustrialCenter P3436 FINISHED
Object Talcahuano E74676 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: Talcahuano | Statement: [Biobío Region, hasIndustrialCenter, Talcahuano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talcahuano
Context triple: [Biobío Region, hasIndustrialCenter, Talcahuano]
  • A. Talcahuano chosen
    Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
  • B. Rancagua
    Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
  • C. Talca
    Talca is a major city in central Chile known as an administrative, commercial, and agricultural hub in the Maule Valley.
  • D. Cauquenes
    Cauquenes is a provincial capital and wine-producing city in central Chile known for its agricultural economy and seismic history.
  • E. Quillota
    Quillota is a Chilean city known for its agricultural production and historical significance within the Valparaíso Region.
  • 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_69a4938bdd3c8190a954a3c11844d9cf completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2b66c908190a52f731119b77a1e completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc5f8bc2081908f7d2435ce43fdc4 completed March 8, 2026, 12:42 a.m.
Created at: March 1, 2026, 7:38 p.m.