Triple

T11855738
Position Surface form Disambiguated ID Type / Status
Subject Marwan Kenzari E282035 entity
Predicate familyName P18 FINISHED
Object Kenzari
Kenzari is a surname most notably associated with Dutch-Tunisian actor Marwan Kenzari, known for his roles in international film and television.
E949057 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: Kenzari | Statement: [Marwan Kenzari, familyName, Kenzari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenzari
Context triple: [Marwan Kenzari, familyName, Kenzari]
  • A. Kensiu
    Kensiu is an endangered Aslian language spoken by an indigenous Semang (Negrito) community in northern Peninsular Malaysia and southern Thailand.
  • B. Adenzai
    Adenzai is a town and administrative settlement located in the Lower Dir District of Khyber Pakhtunkhwa province in Pakistan.
  • C. Hizaori
    Hizaori is the former name of Asaka, a city located in Saitama Prefecture, Japan.
  • D. Kutama
    Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
  • E. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • 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: Kenzari
Triple: [Marwan Kenzari, familyName, Kenzari]
Generated description
Kenzari is a surname most notably associated with Dutch-Tunisian actor Marwan Kenzari, known for his roles in international film and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kenzari
Target entity description: Kenzari is a surname most notably associated with Dutch-Tunisian actor Marwan Kenzari, known for his roles in international film and television.
  • A. Kensiu
    Kensiu is an endangered Aslian language spoken by an indigenous Semang (Negrito) community in northern Peninsular Malaysia and southern Thailand.
  • B. Adenzai
    Adenzai is a town and administrative settlement located in the Lower Dir District of Khyber Pakhtunkhwa province in Pakistan.
  • C. Hizaori
    Hizaori is the former name of Asaka, a city located in Saitama Prefecture, Japan.
  • D. Kutama
    Kutama is a rural village in the Zvimba District of northern Zimbabwe, known primarily as the birthplace of former president Robert Mugabe.
  • E. Katsuragi
    Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a697f4108190af984932d2118472 completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167d9b9e8819093582637941fc5ca completed April 29, 2026, 2:07 a.m.
NEDg Description generation batch_69f17006e6108190b51b20ddf6d2368c completed April 29, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69f17819af5c8190a98db3cd8eff8da2 completed April 29, 2026, 3:16 a.m.
Created at: April 8, 2026, 9:43 p.m.