Triple

T16151134
Position Surface form Disambiguated ID Type / Status
Subject European side of Istanbul E391910 entity
Predicate hasPart P35 FINISHED
Object Eyüpsultan E662873 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: Eyüpsultan | Statement: [European side of Istanbul, hasPart, Eyüpsultan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eyüpsultan
Context triple: [European side of Istanbul, hasPart, Eyüpsultan]
  • A. Eyüpsultan chosen
    Eyüpsultan is a historic district on the European side of Istanbul, renowned for its important Islamic sites, including the Eyüp Sultan Mosque and its adjacent cemetery.
  • B. Fatih
    Fatih is a common Turkish male given name, notably borne by the famous football manager Fatih Terim.
  • C. Eminönü
    Eminönü is a historic waterfront district in Istanbul known for its bustling ferry docks, spice and textile markets, and landmarks like the New Mosque and the Egyptian Bazaar.
  • D. Çandarlı
    Çandarlı is the surname of a prominent Ottoman political family that produced several influential grand viziers in the 14th and 15th centuries.
  • E. Ülker
    Ülker is a major Turkish food company best known for its wide range of confectionery and snack products.
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d981950819087fdacc7879dca97 completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffef2f49081909841a1f9bfbd622b completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 5:01 a.m.