Triple

T15664028
Position Surface form Disambiguated ID Type / Status
Subject Citadis 402 E376638 entity
Predicate usedInCity P4810 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: [Citadis 402, usedInCity, Istanbul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Istanbul
Context triple: [Citadis 402, usedInCity, 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. Istanbul
    Istanbul is a major Ethereum network upgrade that introduced performance improvements, reduced gas costs for certain operations, and enhanced the platform’s overall scalability and security.
  • C. Ankara
    Ankara is the political and administrative center of Turkey, known for hosting the country’s government institutions and foreign embassies.
  • D. Nazilli
    Nazilli is a town and district in Turkey’s Aydın Province, known for its agricultural production and location in the fertile Büyük Menderes River valley.
  • E. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f0f4df08190ad2c5d78e435d8eb completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec6b5ac8190abeb944857d912e6 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:16 a.m.