Triple

T11978563
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Medicine, Ege University E285097 entity
Predicate locatedIn P40 FINISHED
Object Bornova, İzmir E285095 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: Bornova, İzmir | Statement: [Faculty of Medicine, Ege University, locatedIn, Bornova, İzmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bornova, İzmir
Context triple: [Faculty of Medicine, Ege University, locatedIn, Bornova, İzmir]
  • A. Bornova, İzmir chosen
    Bornova, İzmir is a large district of the city of İzmir in western Turkey, known as an important residential, commercial, and educational hub.
  • B. Florya
    Florya is a coastal neighborhood in Istanbul, Turkey, known for its residential areas, seaside promenade, and recreational facilities.
  • C. Yalova
    Yalova is a small coastal city in northwestern Turkey, known for its thermal springs, seaside promenade, and proximity to Istanbul across the Sea of Marmara.
  • D. Güzelyurt
    Güzelyurt is a town in the northwestern part of Cyprus, known for its citrus orchards and archaeological sites.
  • E. Giresun, Turkey
    Giresun, Turkey is a Black Sea coastal city in northeastern Turkey known for its hazelnut production and lush, hilly landscape.
  • 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_69f471f6afc48190856a0f7c486b28aa completed May 1, 2026, 9:27 a.m.
Created at: April 8, 2026, 9:46 p.m.