Triple

T2846254
Position Surface form Disambiguated ID Type / Status
Subject Tram İzmir E62990 entity
Predicate hasLine P35 FINISHED
Object Karşıyaka Tram 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: Karşıyaka Tram | Statement: [Tram İzmir, hasLine, Karşıyaka Tram]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karşıyaka Tram
Context triple: [Tram İzmir, hasLine, Karşıyaka Tram]
  • 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 Metro
    The Istanbul Metro is a rapid transit system serving Istanbul, Turkey, connecting key districts and transport hubs across the city.
  • 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. 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 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_69ab4c407c408190857d25e027155ce9 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf3d00708190966a477fdd855f23 completed March 7, 2026, 8:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8dbdff88190b6c46cfd6ef54bb8 completed March 10, 2026, 9:48 a.m.
Created at: March 6, 2026, 10:02 p.m.