Triple

T3216511
Position Surface form Disambiguated ID Type / Status
Subject Jean Hagen E67409 entity
Predicate familyName P18 FINISHED
Object Verhagen
Verhagen is a Dutch-origin surname borne by various notable individuals in fields such as politics, sports, and the arts.
 E338328 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: Verhagen | Statement: [Jean Hagen, familyName, Verhagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Verhagen
Context triple: [Jean Hagen, familyName, Verhagen]
  • A. Sjaalman
    Sjaalman is a fictional character in Multatuli’s novel "Max Havelaar," serving as an alter ego and narrative device to expose colonial abuses in the Dutch East Indies.
  • B. Molenaar
    Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
  • C. Aeltge Velthuys
    Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
  • D. Marius de Vries
    Marius de Vries is a British composer, producer, and arranger known for his innovative work on film soundtracks and collaborations with prominent pop and electronic artists.
  • E. Yorick van Wageningen
    Yorick van Wageningen is a Dutch actor known internationally for his roles in films such as the 2011 adaptation of "The Girl with the Dragon Tattoo."
  • 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: Verhagen
Triple: [Jean Hagen, familyName, Verhagen]
Generated description
Verhagen is a Dutch-origin surname borne by various notable individuals in fields such as politics, sports, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Verhagen
Target entity description: Verhagen is a Dutch-origin surname borne by various notable individuals in fields such as politics, sports, and the arts.
  • A. Sjaalman
    Sjaalman is a fictional character in Multatuli’s novel "Max Havelaar," serving as an alter ego and narrative device to expose colonial abuses in the Dutch East Indies.
  • B. Molenaar
    Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
  • C. Aeltge Velthuys
    Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
  • D. Marius de Vries
    Marius de Vries is a British composer, producer, and arranger known for his innovative work on film soundtracks and collaborations with prominent pop and electronic artists.
  • E. Yorick van Wageningen
    Yorick van Wageningen is a Dutch actor known internationally for his roles in films such as the 2011 adaptation of "The Girl with the Dragon Tattoo."
  • 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_69ad858b8adc8190ad989712c87a476b completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adab096b588190b22e41a76263ae92 completed March 8, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b26241803c8190aa3254d5887c80f4 completed March 12, 2026, 6:50 a.m.
NEDg Description generation batch_69b2664ddd488190a3edf40fc2dcee18 completed March 12, 2026, 7:07 a.m.
NED2 Entity disambiguation (via description) batch_69b266ca4a90819083ecb16095a2984b completed March 12, 2026, 7:10 a.m.
Created at: March 8, 2026, 3:07 p.m.