Triple

T13251146
Position Surface form Disambiguated ID Type / Status
Subject M1 line E315531 entity
Predicate hasStation P35 FINISHED
Object Kızılay station E1110903 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: Kızılay station | Statement: [M1 line, hasStation, Kızılay station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kızılay station
Context triple: [M1 line, hasStation, Kızılay station]
  • A. Kızılay station chosen
    Kızılay station is a major underground metro hub in central Ankara, Turkey, serving as a key interchange point for multiple lines in the city’s rapid transit network.
  • B. Krasnoselskaya station
    Krasnoselskaya station is a Moscow Metro station known for its early Soviet-era architecture and location on the system’s first metro line.
  • C. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • D. Komsomolskaya station
    Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • E. Komsomolskaya station
    Komsomolskaya station is a prominent Moscow Metro station known for its grand Stalinist architecture and location beneath Komsomolskaya Square, a major railway hub.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f73423c8190932a9edac56df383 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fde15abe6c8190a6212861bbce790e completed May 8, 2026, 1:12 p.m.
Created at: April 9, 2026, 9:24 p.m.