Triple

T12403221
Position Surface form Disambiguated ID Type / Status
Subject Line 4A (Santiago Metro) E296313 entity
Predicate hasStation P35 FINISHED
Object San Ramón station E289059 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: San Ramón station | Statement: [Line 4A (Santiago Metro), hasStation, San Ramón station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Ramón station
Context triple: [Line 4A (Santiago Metro), hasStation, San Ramón station]
  • A. San Ramón station chosen
    San Ramón station is a stop on Santiago, Chile’s Metro system, serving passengers on Line 4A in the southeastern part of the city.
  • B. San Pedro station
    San Pedro station is a railway stop on the Philippine National Railways’ Metro Commuter Line serving the city of San Pedro in Laguna, Philippines.
  • C. San José station
    San José station is a stop on Buenos Aires’ Line E underground, serving passengers in the city’s central area.
  • D. Eduardo Molina station
    Eduardo Molina station is a Mexico City Metro stop named after the nearby Eduardo Molina Avenue, serving commuters in the eastern part of the city.
  • E. Saenz Peña station
    Saenz Peña station is a stop on Line A of the Buenos Aires Underground, serving passengers in the central area of Argentina’s capital city.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d477004819095e65ef6f70c69d9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671852f588190924ded1c0a360b47 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:55 p.m.