Triple

T7303756
Position Surface form Disambiguated ID Type / Status
Subject Hakan Şükür E167922 entity
Predicate givenName P17 FINISHED
Object Hakan
Hakan is a common Turkish male given name, often associated with notable figures such as former footballer and politician Hakan Şükür.
 E654531 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: Hakan | Statement: [Hakan Şükür, givenName, Hakan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hakan
Context triple: [Hakan Şükür, givenName, Hakan]
  • A. Johan
    Johan is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • B. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • C. Johan
    Johan is the given first name of the Swedish playwright and novelist August Strindberg.
  • D. Mikael
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • E. Haraldsen
    Haraldsen is a Norwegian surname most notably borne by Queen Sonja of Norway before her marriage into the royal family.
  • 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: Hakan
Triple: [Hakan Şükür, givenName, Hakan]
Generated description
Hakan is a common Turkish male given name, often associated with notable figures such as former footballer and politician Hakan Şükür.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hakan
Target entity description: Hakan is a common Turkish male given name, often associated with notable figures such as former footballer and politician Hakan Şükür.
  • A. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • B. Johan
    Johan is the given first name of the Swedish playwright and novelist August Strindberg.
  • C. Johan
    Johan is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • D. Mikael
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • E. Haraldsen
    Haraldsen is a Norwegian surname most notably borne by Queen Sonja of Norway before her marriage into the royal family.
  • 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_69c6888c820881909fc68f689fe1c251 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebb352ec8190846eff044e08805e completed March 27, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e55bfccc8190a46067c60c3c1a3f completed March 28, 2026, 2:27 p.m.
NEDg Description generation batch_69c7e5fbe8a8819083a892f4e54013eb completed March 28, 2026, 2:30 p.m.
NED2 Entity disambiguation (via description) batch_69c7e69ca1ac8190a398da894c6cc04e completed March 28, 2026, 2:33 p.m.
Created at: March 27, 2026, 3:01 p.m.