Triple

T21199077
Position Surface form Disambiguated ID Type / Status
Subject Nicolás Arriola station E522402 entity
Predicate followingStationOnLine1 P136756 FINISHED
Object Miguel Grau station 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: Miguel Grau station | Statement: [Nicolás Arriola station, followingStationOnLine1, Miguel Grau station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miguel Grau station
Context triple: [Nicolás Arriola station, followingStationOnLine1, Miguel Grau station]
  • A. Miguel Grau station chosen
    Miguel Grau station is a passenger stop on Line 1 of the Lima Metro rapid transit system in Lima, Peru.
  • B. O’Higgins Station
    O’Higgins Station is a Chilean Antarctic research base located on the Antarctic Peninsula, used primarily for scientific studies and maintaining Chile’s presence in the region.
  • C. Miramar station
    Miramar station is a passenger rail station on the Valparaíso Metro system in Chile, serving the coastal city of Viña del Mar.
  • D. Baquedano station
    Baquedano station is a major interchange hub in the Santiago Metro system, connecting multiple lines and serving as a key access point to the central area of Chile’s capital.
  • E. Lima station
    Lima station is an underground metro station on Buenos Aires’ Line A, serving the city’s central area.
  • 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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7342fe3a08190b7ed2cadf60091a8 completed April 21, 2026, 8:24 a.m.
Created at: April 16, 2026, 3:16 p.m.