Triple

T7280938
Position Surface form Disambiguated ID Type / Status
Subject Beyazıt Campus E163143 entity
Predicate locatedIn P40 FINISHED
Object Beyazıt E646419 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: Beyazıt | Statement: [Beyazıt Campus, locatedIn, Beyazıt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beyazıt
Context triple: [Beyazıt Campus, locatedIn, Beyazıt]
  • A. Nişantaşı
    Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
  • B. Brusa Bezistan
    Brusa Bezistan is a historic covered market building in Sarajevo’s old bazaar area, known for its Ottoman-era architecture and traditional trading stalls.
  • C. Beştepe
    Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
  • D. Beyazıt Square chosen
    Beyazıt Square is a historic public square in Istanbul, Turkey, known for its proximity to Istanbul University and several important Ottoman-era landmarks.
  • E. Ortaköy
    Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb34fe0c8190a642fd3339f0cacd completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa6d84b88190916b1d9ddb0d1d0d completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 2:59 p.m.