Triple

T7791145
Position Surface form Disambiguated ID Type / Status
Subject Yılmaz Büyükerşen E180181 entity
Predicate givenName P17 FINISHED
Object Yılmaz
Yılmaz is a Turkish given name commonly used for men.
 E180181 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: Yılmaz | Statement: [Yılmaz Büyükerşen, givenName, Yılmaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yılmaz
Context triple: [Yılmaz Büyükerşen, givenName, Yılmaz]
  • A. Yılmaz Büyükerşen
    Yılmaz Büyükerşen is a Turkish academic, sculptor, and long-serving mayor of Eskişehir known for transforming the city through innovative urban and cultural projects.
  • B. 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.
  • C. Fuat
    Fuat is a Turkish masculine given name commonly borne by notable figures in politics, academia, and the arts.
  • D. Ismail Ankaravi
    Ismail Ankaravi was an Ottoman-era Mevlevi scholar and Sufi commentator best known for his influential exegesis on Rumi’s Mathnawi.
  • E. 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."
  • 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: Yılmaz
Triple: [Yılmaz Büyükerşen, givenName, Yılmaz]
Generated description
Yılmaz is a Turkish given name commonly used for men.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yılmaz
Target entity description: Yılmaz is a Turkish given name commonly used for men.
  • A. Yılmaz Büyükerşen chosen
    Yılmaz Büyükerşen is a Turkish academic, sculptor, and long-serving mayor of Eskişehir known for transforming the city through innovative urban and cultural projects.
  • B. 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.
  • C. Fuat
    Fuat is a Turkish masculine given name commonly borne by notable figures in politics, academia, and the arts.
  • D. Ismail Ankaravi
    Ismail Ankaravi was an Ottoman-era Mevlevi scholar and Sufi commentator best known for his influential exegesis on Rumi’s Mathnawi.
  • E. 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."
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae9375dcc8190a6cb696c02aeceb7 completed March 30, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb59f230d48190ad4cb08e9e73f19e completed March 31, 2026, 5:21 a.m.
NEDg Description generation batch_69cb5f1afe0c8190916c7a9b2eab9270 completed March 31, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_69cb764973f88190964f91ee7e3fdc06 completed March 31, 2026, 7:22 a.m.
Created at: March 30, 2026, 4:30 p.m.