Triple

T7196769
Position Surface form Disambiguated ID Type / Status
Subject Ekrem Akurgal E168634 entity
Predicate givenName P17 FINISHED
Object Ekrem
Ekrem is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
 E650378 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: Ekrem | Statement: [Ekrem Akurgal, givenName, Ekrem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ekrem
Context triple: [Ekrem Akurgal, givenName, Ekrem]
  • A. Kerim Bey
    Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
  • B. Güntekin
    Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
  • C. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • D. Emre
    Emre is a Turkish surname and given name most notably associated with Yunus Emre, a revered 13th–14th century Sufi poet and mystic.
  • E. Selim Işık
    Selim Işık is a central, tragicomic character in Oğuz Atay’s novel "Tutunamayanlar," symbolizing the alienated intellectual who cannot adapt to modern Turkish society.
  • 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: Ekrem
Triple: [Ekrem Akurgal, givenName, Ekrem]
Generated description
Ekrem is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ekrem
Target entity description: Ekrem is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
  • A. Kerim Bey
    Kerim Bey is a charismatic and resourceful MI6 ally in the James Bond series, best known for assisting Bond in Istanbul in the film and novel "From Russia, with Love."
  • B. Güntekin
    Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
  • C. Ahmet
    Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
  • D. Emre
    Emre is a Turkish surname and given name most notably associated with Yunus Emre, a revered 13th–14th century Sufi poet and mystic.
  • E. Selim Işık
    Selim Işık is a central, tragicomic character in Oğuz Atay’s novel "Tutunamayanlar," symbolizing the alienated intellectual who cannot adapt to modern Turkish society.
  • 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e928ecdc8190a7f3feaf6d28781b completed March 27, 2026, 8:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbe7d42c8190915fd0713523cbb0 completed March 28, 2026, 12:39 p.m.
NEDg Description generation batch_69c7cc787a9881908c44b1b94b748e9c completed March 28, 2026, 12:41 p.m.
NED2 Entity disambiguation (via description) batch_69c7cd0eb36c8190bc8e4265033d214f completed March 28, 2026, 12:43 p.m.
Created at: March 27, 2026, 2:51 p.m.