Triple

T8597811
Position Surface form Disambiguated ID Type / Status
Subject Beykoz E203594 entity
Predicate borders P224 FINISHED
Object Sarıyer E171451 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: Sarıyer | Statement: [Beykoz, borders, Sarıyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarıyer
Context triple: [Beykoz, borders, Sarıyer]
  • A. Sarıyer chosen
    Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
  • B. Beykoz
    Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
  • C. Üsküdar
    Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
  • D. Kadıköy
    Kadıköy is a historic district on the Asian side of Istanbul, Turkey, known for its ancient roots (including the site of the Council of Chalcedon), vibrant cultural life, and bustling waterfront.
  • E. Çekmeköy
    Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
  • 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_69ca832b56948190ba751cec255308f1 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46cacbe88190b95beeedc9f480b0 completed March 31, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d07719ee048190ac4045017d89e938 completed April 4, 2026, 2:27 a.m.
Created at: March 30, 2026, 6:24 p.m.