Triple

T12862949
Position Surface form Disambiguated ID Type / Status
Subject Fahrettin Altay station E307641 entity
Predicate partOf P40 FINISHED
Object İzmir Metro E62383 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: İzmir Metro | Statement: [Fahrettin Altay station, partOf, İzmir Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmir Metro
Context triple: [Fahrettin Altay station, partOf, İzmir Metro]
  • A. Izmir Metro chosen
    Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
  • B. Istanbul Metro
    The Istanbul Metro is a rapid transit system serving Istanbul, Turkey, connecting key districts and transport hubs across the city.
  • C. İzmir Metro Basmane station
    İzmir Metro Basmane station is an underground rapid transit stop in central İzmir that provides metro access and interchange with the adjacent historic Basmane railway station.
  • D. Ankara Metro
    Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
  • E. Tram Izmir
    Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708cf6b48190886a99e04d85d348 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1af38248190a85d0fa3a26c3d08 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 5:37 p.m.