Triple

T11979149
Position Surface form Disambiguated ID Type / Status
Subject Gulf of Izmir E285111 entity
Predicate formsHarborOf P3007 FINISHED
Object Izmir 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: Izmir | Statement: [Gulf of Izmir, formsHarborOf, Izmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Izmir
Context triple: [Gulf of Izmir, formsHarborOf, Izmir]
  • A. Izmir chosen
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • B. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • C. 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.
  • D. 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.
  • E. 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.
  • 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_69f655531d708190b351b98064afec3f completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:46 p.m.