Triple

T11337998
Position Surface form Disambiguated ID Type / Status
Subject Michael Zegen E268520 entity
Predicate familyName P18 FINISHED
Object Zegen
Zegen is a surname most notably associated with American actor Michael Zegen, known for his roles in television and film.
 E919863 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: Zegen | Statement: [Michael Zegen, familyName, Zegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zegen
Context triple: [Michael Zegen, familyName, Zegen]
  • A. Zigra
    Zigra is a monstrous alien shark-like kaiju from the Gamera film series, known for invading Earth and battling the giant turtle guardian.
  • B. Zabdeno
    Zabdeno is a viral vector vaccine that uses a human adenovirus serotype 26 platform to provide protection against Ebola virus disease.
  • C. Zannanza
    Zannanza was a Hittite prince, best known for his ill-fated journey to marry the Egyptian widow-queen that sparked a major diplomatic crisis between the Hittite and Egyptian empires.
  • D. Zvenigora
    Zvenigora is a 1928 Soviet silent film by Ukrainian director Alexander Dovzhenko, celebrated for its poetic, avant-garde style and exploration of Ukrainian history and folklore.
  • E. Dazaga
    Dazaga is a Saharan language spoken primarily by the Daza (Gorane) people across parts of Chad, Niger, Libya, and Sudan.
  • 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: Zegen
Triple: [Michael Zegen, familyName, Zegen]
Generated description
Zegen is a surname most notably associated with American actor Michael Zegen, known for his roles in television and film.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zegen
Target entity description: Zegen is a surname most notably associated with American actor Michael Zegen, known for his roles in television and film.
  • A. Zigra
    Zigra is a monstrous alien shark-like kaiju from the Gamera film series, known for invading Earth and battling the giant turtle guardian.
  • B. Zabdeno
    Zabdeno is a viral vector vaccine that uses a human adenovirus serotype 26 platform to provide protection against Ebola virus disease.
  • C. Zannanza
    Zannanza was a Hittite prince, best known for his ill-fated journey to marry the Egyptian widow-queen that sparked a major diplomatic crisis between the Hittite and Egyptian empires.
  • D. Zvenigora
    Zvenigora is a 1928 Soviet silent film by Ukrainian director Alexander Dovzhenko, celebrated for its poetic, avant-garde style and exploration of Ukrainian history and folklore.
  • E. Dazaga
    Dazaga is a Saharan language spoken primarily by the Daza (Gorane) people across parts of Chad, Niger, Libya, and Sudan.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea008b5081908e6c6c6fc29ef936 completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5432abfd081909d1bbf6460643fb9 completed April 19, 2026, 9:03 p.m.
NEDg Description generation batch_69e5474879088190990468d960b26739 completed April 19, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69e54eccdd3881908536ee3f9f4ef516 completed April 19, 2026, 9:53 p.m.
Created at: April 8, 2026, 9:33 p.m.