Triple

T11978375
Position Surface form Disambiguated ID Type / Status
Subject Menderes E285092 entity
Predicate locatedNear P294 FINISHED
Object city of 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: city of İzmir | Statement: [Menderes, locatedNear, city of İzmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of İzmir
Context triple: [Menderes, locatedNear, city of İzmir]
  • A. Izmir chosen
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • B. Izmir Metropolitan Municipality
    Izmir Metropolitan Municipality is the principal local government authority responsible for administering and providing public services in the city and greater metropolitan area of Izmir, Turkey.
  • C. 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.
  • D. 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.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f63e99d88190b718217005464954 completed May 2, 2026, 1:03 p.m.
Created at: April 8, 2026, 9:46 p.m.