Triple

T26547117
Position Surface form Disambiguated ID Type / Status
Subject Osmanlı Devleti’nin Saray Teşkilâtı E671565 entity
Predicate eleAlır P164843 FINISHED
Object Enderun teşkilatı
Enderun teşkilatı, Osmanlı İmparatorluğu’nda saray içinde devlet adamı ve bürokrat yetiştiren seçkin bir eğitim ve yönetim kurumuydu.
 E1731531 NE FINISHED

How this triple was built (3 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: Enderun teşkilatı | Statement: [Osmanlı Devleti’nin Saray Teşkilâtı, eleAlır, Enderun teşkilatı]
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: Enderun teşkilatı
Triple: [Osmanlı Devleti’nin Saray Teşkilâtı, eleAlır, Enderun teşkilatı]
Generated description
Enderun teşkilatı, Osmanlı İmparatorluğu’nda saray içinde devlet adamı ve bürokrat yetiştiren seçkin bir eğitim ve yönetim kurumuydu.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: eleAlır
Context triple: [Osmanlı Devleti’nin Saray Teşkilâtı, eleAlır, Enderun teşkilatı]
  • A. eleAldığıKavram
    Indicates a relationship where an entity receives, adopts, or takes on a particular concept or notion.
  • B. éA
    Indicates a directed association or influence from one entity toward another, where the first entity acts upon, affects, or is related to the second in a specified manner.
  • C. eve
    Indicates a relationship where one entity is the evening or night-time counterpart, phase, or occurrence associated with another entity.
  • D. alan
    Indicates that one entity is named or identified as Alan.
  • E. era
    Indicates that something existed, occurred, or was valid during a specified historical or temporal period.
  • F. None of above. chosen

Provenance (7 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_69eeb32163f08190af5f81282738e27a completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f650fc44e48190bc0e0a935eac62a6 completed May 2, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c819b32c8190aaca1f8db245732e completed May 23, 2026, 3:30 p.m.
NEDg Description generation batch_6a11c966cc288190804da81d474872dd completed May 23, 2026, 3:36 p.m.
NED2 Entity disambiguation (via description) batch_6a11ca61b1408190ab4bda33e53cb27c completed May 23, 2026, 3:40 p.m.
PD Predicate disambiguation batch_69f64cab1f648190a2a9460690d18a37 completed May 2, 2026, 7:12 p.m.
PDg Predicate description generation batch_69f650c466b881908954e43bfebae8a4 completed May 2, 2026, 7:30 p.m.
Created at: April 27, 2026, 1:45 a.m.