Triple

T11181903
Position Surface form Disambiguated ID Type / Status
Subject Haluk Bilginer E264561 entity
Predicate birthPlace P1 FINISHED
Object İzmir E10416 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 | Statement: [Haluk Bilginer, birthPlace, İzmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmir
Context triple: [Haluk Bilginer, birthPlace, İzmir]
  • A. Izmir chosen
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • B. İzmit
    İzmit is a city in northwestern Turkey on the Gulf of İzmit, historically significant as the site of ancient Nicomedia and an important industrial and transportation hub near Istanbul.
  • C. Denizli
    Denizli is a major industrial and commercial city in western Turkey, known for its textile production and proximity to the famous Pamukkale travertine terraces.
  • D. Nazilli
    Nazilli is a town and district in Turkey’s Aydın Province, known for its agricultural production and location in the fertile Büyük Menderes River valley.
  • E. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8a7f35481909f35feb94ef10e80 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc1ed3d0819089c6885f21350298 completed April 19, 2026, 12:35 p.m.
Created at: April 8, 2026, 9:29 p.m.