Triple

T7840482
Position Surface form Disambiguated ID Type / Status
Subject İzmir Province E181790 entity
Predicate contains P35 FINISHED
Object Menemen E311742 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: Menemen | Statement: [İzmir Province, contains, Menemen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Menemen
Context triple: [İzmir Province, contains, Menemen]
  • A. Menemen chosen
    Menemen is a district and town in İzmir Province, Turkey, known for its agricultural production and as part of the greater İzmir metropolitan area.
  • B. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • C. Toprakkale
    Toprakkale is an ancient fortress and archaeological site in eastern Turkey that served as a significant center of the Iron Age Kingdom of Urartu.
  • D. Kanık
    Kanık is the surname of the influential Turkish poet Orhan Veli Kanık, a leading figure in modern Turkish literature and the Garip movement.
  • E. Karabük
    Karabük is an industrial city in northern Turkey best known for its historic iron and steel industry and its proximity to the UNESCO-listed Ottoman town of Safranbolu.
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb14c589748190b34d0911d373e194 completed March 31, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd3394b5408190a3d540b5eede456e completed April 1, 2026, 3:02 p.m.
Created at: March 30, 2026, 4:47 p.m.