Triple

T2837346
Position Surface form Disambiguated ID Type / Status
Subject Izmir International Fair E62381 entity
Predicate hasEconomicImpactOn P2313 FINISHED
Object Izmir E10416 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: Izmir | Statement: [Izmir International Fair, hasEconomicImpactOn, Izmir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Izmir
Context triple: [Izmir International Fair, hasEconomicImpactOn, Izmir]
  • A. Izmir chosen
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • B. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • C. İzmit
    İzmit is a city in northwestern Turkey on the Gulf of İzmit, historically significant as the site of ancient Nicomedia and an important industrial and transportation hub near Istanbul.
  • D. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • E. Antalya
    Antalya is a major resort city on Turkey’s Mediterranean coast, known for its beaches, historic old town, and role as a gateway to the Turkish Riviera.
  • 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_69ab4c3c39188190955b9c49d98463d8 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdeede0488190a9782f55b57559ee completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc4b8f688190827dfedda7a55828 completed March 11, 2026, 5:23 a.m.
Created at: March 6, 2026, 10:01 p.m.