Triple

T20572685
Position Surface form Disambiguated ID Type / Status
Subject Ayşe E505140 entity
Predicate hasDiminutiveOrNicknameForm P56482 FINISHED
Object Ayşegül (compound name)
Ayşegül is a Turkish feminine compound given name, typically formed by combining "Ayşe" with "Gül," meaning "rose."
 E1439109 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: Ayşegül (compound name) | Statement: [Ayşe, hasDiminutiveOrNicknameForm, Ayşegül (compound name)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ayşegül (compound name)
Context triple: [Ayşe, hasDiminutiveOrNicknameForm, Ayşegül (compound name)]
  • A. Güls
    Güls is a district of the German city of Koblenz, situated along the Moselle River and known for its winegrowing and scenic riverside setting.
  • B. Münevver
    Münevver is a Turkish feminine given name historically borne by several notable women in Turkish literature and arts.
  • C. Zeynep Alasya
    Zeynep Alasya is a Turkish singer best known for performing the opening theme of the historical TV series "Diriliş: Ertuğrul."
  • D. Ağaoğlu
    Ağaoğlu is a Turkish surname most prominently associated with figures such as novelist and playwright Adalet Ağaoğlu.
  • E. Nergiz
    Nergiz is a neighborhood within the Karşıyaka district of İzmir, Turkey, known as a residential and commercial area on the city’s northern shore.
  • 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: Ayşegül (compound name)
Triple: [Ayşe, hasDiminutiveOrNicknameForm, Ayşegül (compound name)]
Generated description
Ayşegül is a Turkish feminine compound given name, typically formed by combining "Ayşe" with "Gül," meaning "rose."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ayşegül (compound name)
Target entity description: Ayşegül is a Turkish feminine compound given name, typically formed by combining "Ayşe" with "Gül," meaning "rose."
  • A. Güls
    Güls is a district of the German city of Koblenz, situated along the Moselle River and known for its winegrowing and scenic riverside setting.
  • B. Münevver
    Münevver is a Turkish feminine given name historically borne by several notable women in Turkish literature and arts.
  • C. Zeynep Alasya
    Zeynep Alasya is a Turkish singer best known for performing the opening theme of the historical TV series "Diriliş: Ertuğrul."
  • D. Ağaoğlu
    Ağaoğlu is a Turkish surname most prominently associated with figures such as novelist and playwright Adalet Ağaoğlu.
  • E. Nergiz
    Nergiz is a neighborhood within the Karşıyaka district of İzmir, Turkey, known as a residential and commercial area on the city’s northern shore.
  • 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_69e0b4b721588190993ac7b0a9be2736 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a906f0508190ac698233738f4452 completed April 20, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08ace448d48190a2a225a3cb4b5cf5 completed May 16, 2026, 5:44 p.m.
NEDg Description generation batch_6a08ae5320d08190b8ce6fbe4909af18 completed May 16, 2026, 5:50 p.m.
NED2 Entity disambiguation (via description) batch_6a08aed4a9908190bf7bd5f0147ff6f2 completed May 16, 2026, 5:52 p.m.
Created at: April 16, 2026, 11:39 a.m.