Triple

T4974621
Position Surface form Disambiguated ID Type / Status
Subject Clifford Chance E111734 entity
Predicate hasOfficeIn P1268 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: [Clifford Chance, hasOfficeIn, Istanbul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Istanbul
Context triple: [Clifford Chance, hasOfficeIn, 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_69bd441a0eb481908050fa4273b19eae completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd722e77208190833dc760a57428d5 completed March 20, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea46c12c481909aed42f9b45cde81 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:33 p.m.