Triple

T681443
Position Surface form Disambiguated ID Type / Status
Subject Royal Air Maroc E13189 entity
Predicate servesCity P82 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: [Royal Air Maroc, servesCity, Istanbul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Istanbul
Context triple: [Royal Air Maroc, servesCity, 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a06e294c8190873116a3253e04f9 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6732d5a208190ac9e0f3d0fab7a0d completed March 3, 2026, 5:35 a.m.
Created at: March 1, 2026, 7:36 p.m.