Triple

T501749
Position Surface form Disambiguated ID Type / Status
Subject Izmir E10416 entity
Predicate hasHistoricDistrict P295 FINISHED
Object Kemeraltı
Kemeraltı is a historic bazaar and commercial district in İzmir, Turkey, known for its traditional markets, Ottoman-era architecture, and vibrant street life.
 E10416 NE FINISHED

How this triple was built (4 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: Kemeraltı | Statement: [Izmir, hasHistoricDistrict, Kemeraltı]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kemeraltı
Context triple: [Izmir, hasHistoricDistrict, Kemeraltı]
  • A. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • B. 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.
  • C. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • D. Izmir
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • E. Yalova
    Yalova is a small coastal city in northwestern Turkey, known for its thermal springs, seaside promenade, and proximity to Istanbul across the Sea of Marmara.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kemeraltı
Triple: [Izmir, hasHistoricDistrict, Kemeraltı]
Generated description
Kemeraltı is a historic bazaar and commercial district in İzmir, Turkey, known for its traditional markets, Ottoman-era architecture, and vibrant street life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kemeraltı
Target entity description: Kemeraltı is a historic bazaar and commercial district in İzmir, Turkey, known for its traditional markets, Ottoman-era architecture, and vibrant street life.
  • A. Trabzon
    Trabzon is a historic city in northeastern Turkey that serves as a major Black Sea port and regional cultural and commercial center.
  • B. 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.
  • C. Samsun
    Samsun is a major Turkish port city on the Black Sea coast, known as an important regional hub for maritime trade and industry.
  • D. Izmir chosen
    Izmir is a major Turkish coastal city known as an important commercial and cultural hub on the Aegean Sea.
  • E. Yalova
    Yalova is a small coastal city in northwestern Turkey, known for its thermal springs, seaside promenade, and proximity to Istanbul across the Sea of Marmara.
  • F. None of above.

Provenance (5 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_69a2e848adf881908e5e04f7af030093 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f131e2148190afd43402f505c73e completed Feb. 28, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4a14aab308190b12deb3509e9715e completed March 1, 2026, 8:27 p.m.
NEDg Description generation batch_69a4a27e8b7c8190991d3d5dc44c6913 completed March 1, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69a4a2d68b688190a5ec28394356d76c completed March 1, 2026, 8:34 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.