Triple

T22347235
Position Surface form Disambiguated ID Type / Status
Subject Ruta 68 E552424 entity
Predicate terminusB P388 FINISHED
Object Valparaíso NE NERFINISHED

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: Valparaíso | Statement: [Ruta 68, terminusB, Valparaíso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valparaíso
Context triple: [Ruta 68, terminusB, Valparaíso]
  • A. Valparaíso
    Valparaíso is a rural municipality located in the Caquetá Department of southern Colombia, known for its Amazonian landscapes and agricultural economy.
  • B. Valparaíso chosen
    Valparaíso is a major Pacific port city in central Chile, renowned for its steep hillsides, colorful houses, historic funiculars, and UNESCO-listed historic quarter.
  • C. 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.
  • D. La Serena
    La Serena is a comarca in the Province of Badajoz in Extremadura, Spain, known for its rural landscapes, sheep farming, and production of La Serena cheese.
  • E. Santiago
    Santiago is a charismatic bohemian performer and friend of Christian in *Moulin Rouge! The Musical*, contributing comic relief, passion, and artistic flair to the story.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4a0ad08190a385b4d343cf6524 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f157995bec819080b8d05fa88704ed completed April 29, 2026, 12:58 a.m.
Created at: April 16, 2026, 8:43 p.m.