Triple

T2837382
Position Surface form Disambiguated ID Type / Status
Subject Konak E62382 entity
Predicate traversedBy P225 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: [Konak, traversedBy, İzmir Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmir Metro
Context triple: [Konak, traversedBy, 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. Ankara Metro
    Ankara Metro is the rapid transit system serving Turkey's capital city, providing urban rail transportation across Ankara and its surrounding districts.
  • D. 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.
  • E. Tehran Metro
    Tehran Metro is the rapid transit system serving Iran’s capital, providing extensive urban and suburban rail transport across the Tehran metropolitan area.
  • 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeede0488190a9782f55b57559ee completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8cbaa4081909ff4e9fdf590e352 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 10:01 p.m.