Triple

T8862038
Position Surface form Disambiguated ID Type / Status
Subject Beylerbeyi E210912 entity
Predicate governedBy P46 FINISHED
Object Üsküdar Municipality 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 Municipality | Statement: [Beylerbeyi, governedBy, Üsküdar Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Üsküdar Municipality
Context triple: [Beylerbeyi, governedBy, Üsküdar Municipality]
  • 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. Beykoz
    Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
  • C. Şişli district
    Şişli district is a central and densely populated area on Istanbul’s European side, known for its commercial centers, business districts, and historic neighborhoods.
  • D. Marmara District
    Marmara District is an administrative district in Balıkesir Province, Turkey, encompassing several islands in the Sea of Marmara, including Avşa Island.
  • E. 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.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610263048190931bb2c3ac573a08 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69d100a931988190aaff56f16057ea90 completed April 4, 2026, 12:14 p.m.
Created at: March 30, 2026, 6:50 p.m.