Triple

T10795221
Position Surface form Disambiguated ID Type / Status
Subject Süleyman Soylu E254686 entity
Predicate familyName P18 FINISHED
Object Soylu
Soylu is a Turkish surname most prominently associated with Süleyman Soylu, a notable Turkish politician and former Minister of the Interior.
 E885514 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: Soylu | Statement: [Süleyman Soylu, familyName, Soylu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Soylu
Context triple: [Süleyman Soylu, familyName, Soylu]
  • A. Proliv Soyya
    Proliv Soyya is the Russian name for the La Pérouse Strait, a narrow sea passage separating the Japanese island of Hokkaido from Russia’s Sakhalin Island.
  • B. Soyembika
    Soyembika was a Tatar princess and regent of the Khanate of Kazan in the 16th century, remembered as a symbol of Tatar statehood and resistance.
  • C. Sosanya
    Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
  • D. Sulien
    Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
  • E. Sula Rasa
    Sula Rasa is a premium Indian red wine produced by Sula Vineyards, known for its rich, full-bodied character and oak-aged complexity.
  • 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: Soylu
Triple: [Süleyman Soylu, familyName, Soylu]
Generated description
Soylu is a Turkish surname most prominently associated with Süleyman Soylu, a notable Turkish politician and former Minister of the Interior.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Soylu
Target entity description: Soylu is a Turkish surname most prominently associated with Süleyman Soylu, a notable Turkish politician and former Minister of the Interior.
  • A. Proliv Soyya
    Proliv Soyya is the Russian name for the La Pérouse Strait, a narrow sea passage separating the Japanese island of Hokkaido from Russia’s Sakhalin Island.
  • B. Soyembika
    Soyembika was a Tatar princess and regent of the Khanate of Kazan in the 16th century, remembered as a symbol of Tatar statehood and resistance.
  • C. Sosanya
    Sosanya is a surname most notably associated with British actress Nina Sosanya, known for her extensive work in television, film, and theatre.
  • D. Sulien
    Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
  • E. Sula Rasa
    Sula Rasa is a premium Indian red wine produced by Sula Vineyards, known for its rich, full-bodied character and oak-aged complexity.
  • F. None of above. chosen

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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733321dd881909dcd4224dfa9822a completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69de5654e2c48190a8f078b8164707e2 completed April 14, 2026, 2:59 p.m.
NEDg Description generation batch_69de5eae7ab88190a0c512cfe61e3458 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de60907e1081908405b6d71adbd388 completed April 14, 2026, 3:43 p.m.
Created at: April 8, 2026, 9:17 p.m.