Triple

T12314094
Position Surface form Disambiguated ID Type / Status
Subject Line 10-Turquesa E293554 entity
Predicate connects P390 FINISHED
Object Rio Grande da Serra station E976509 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: Rio Grande da Serra station | Statement: [Line 10-Turquesa, connects, Rio Grande da Serra station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rio Grande da Serra station
Context triple: [Line 10-Turquesa, connects, Rio Grande da Serra station]
  • A. Rio Grande da Serra station chosen
    Rio Grande da Serra station is a commuter rail terminus in the São Paulo metropolitan region, serving as the endpoint of CPTM’s Line 10–Turquesa.
  • B. Cabo Ruivo station
    Cabo Ruivo station is a Lisbon Metro stop on the Red Line serving the Parque das Nações and eastern Lisbon area.
  • C. Santa Isabel station
    Santa Isabel station is an underground stop on Santiago, Chile’s Metro system, serving Line 5 in the central area of the city.
  • D. Guadalupe station
    Guadalupe station is a passenger rail station in Guadalupe, California, serving as a local stop on regional commuter and intercity rail services.
  • E. Guadalupe station
    Guadalupe station is an elevated rapid transit stop on Manila's MRT Line 3 serving the Guadalupe area in Makati, Philippines.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f03d3c88190baedffb83465bff8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a9d50b081908f0bdb7a2ca2832a completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.