Triple

T10766708
Position Surface form Disambiguated ID Type / Status
Subject Calouste Gulbenkian E253972 entity
Predicate placeOfBirth P1 FINISHED
Object Üsküdar E174017 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: Üsküdar | Statement: [Calouste Gulbenkian, placeOfBirth, Üsküdar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Üsküdar
Context triple: [Calouste Gulbenkian, placeOfBirth, Üsküdar]
  • A. Üsküdar chosen
    Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
  • B. 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.
  • C. Sarıyer
    Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
  • D. 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.
  • E. Beykoz
    Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
  • 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_69d6aa5f54f4819082d0bbcb6f8797e6 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d7322d3a9c81909e58f6064643b814 completed April 9, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69de55cbbecc81908c2ddf2739ce7ffe completed April 14, 2026, 2:57 p.m.
Created at: April 8, 2026, 9:16 p.m.