Triple

T22321598
Position Surface form Disambiguated ID Type / Status
Subject Beylik of Aydın E551799 entity
Predicate notablePort P6498 FINISHED
Object İzmir NE NERFINISHED

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: [Beylik of Aydın, notablePort, İzmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: İzmir
Context triple: [Beylik of Aydın, notablePort, 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 (2 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_69e11e4776588190abb21e5cea79973f completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15764d3a48190af79ce4642b7f563 completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:42 p.m.