Triple

T11738673
Position Surface form Disambiguated ID Type / Status
Subject J. Ruiz station E279095 entity
Predicate adjacentStation P5707 FINISHED
Object V. Mapa station E277586 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: V. Mapa station | Statement: [J. Ruiz station, adjacentStation, V. Mapa station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: V. Mapa station
Context triple: [J. Ruiz station, adjacentStation, V. Mapa station]
  • A. V. Mapa station chosen
    V. Mapa station is an elevated Manila Light Rail Transit Line 2 station located in the Santa Mesa area of Manila, Philippines.
  • B. Obelya station
    Obelya station is a metro station in Sofia, Bulgaria, serving as an interchange point between lines of the Sofia Metro network.
  • C. Viau station
    Viau station is a Montreal Metro station on the Green Line, serving the Hochelaga-Maisonneuve area and providing access to nearby attractions such as the Olympic Park.
  • D. Nadezhda station
    Nadezhda station is a metro station on the Sofia Metro system in Sofia, Bulgaria, serving the Nadezhda residential district.
  • E. Frunzenskaya station
    Frunzenskaya station is a Moscow Metro station known for its deep-level construction and classic Soviet-era architectural design.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4ef1c4881909ad36dc27b1fe193 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019c339cc81909967ecfa234e4ab8 completed April 28, 2026, 2:21 a.m.
Created at: April 8, 2026, 9:41 p.m.