Triple

T12690725
Position Surface form Disambiguated ID Type / Status
Subject Halkapınar E303195 entity
Predicate servedBy P82 FINISHED
Object Tram İzmir E62990 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: Tram İzmir | Statement: [Halkapınar, servedBy, Tram İzmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tram İzmir
Context triple: [Halkapınar, servedBy, Tram İzmir]
  • A. Tram Izmir chosen
    Tram Izmir is a modern light rail tram network serving the Turkish city of İzmir as part of its urban public transportation system.
  • B. Istanbul tram network
    The Istanbul tram network is a modern urban rail system that forms a key part of the city’s public transport, linking major districts on the European side and connecting seamlessly with metro, bus, and ferry services.
  • C. Izmir Metro
    Izmir Metro is a rapid transit rail system serving the city of Izmir, Turkey, providing high-capacity urban transportation across key districts.
  • D. Istanbul Metrobus
    Istanbul Metrobus is a bus rapid transit system in Istanbul that runs on dedicated lanes to provide fast, high-capacity public transportation across the city.
  • E. Tram 18
    Tram 18 is a tram line in Geneva’s public transport system that connects key districts within the city and its surrounding areas.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961dabb38819087738361f9de8066 completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eafd4f8819083f20d142e9115ae completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:22 p.m.