Triple

T2238217
Position Surface form Disambiguated ID Type / Status
Subject Sümeyye Erdoğan E49331 entity
Predicate residence P75 FINISHED
Object Istanbul E4825 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: Istanbul | Statement: [Sümeyye Erdoğan, residence, Istanbul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Istanbul
Context triple: [Sümeyye Erdoğan, residence, Istanbul]
  • A. Istanbul chosen
    Istanbul is a transcontinental metropolis straddling Europe and Asia, renowned as Turkey’s cultural and economic hub and for its rich history as the former capital of the Byzantine and Ottoman Empires.
  • B. Ankara
    Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
  • C. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • D. Izmir
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • E. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc096c7748190a545cc9b229bde62 completed March 7, 2026, 6:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69af989af058819082c35bee706d0ea0 completed March 10, 2026, 4:05 a.m.
Created at: March 4, 2026, 7:47 p.m.