Triple

T11484380
Position Surface form Disambiguated ID Type / Status
Subject A. G. Visser E272236 entity
Predicate familyName P18 FINISHED
Object Visser
Visser is a common Dutch surname borne by various notable individuals across fields such as sports, academia, and the arts.
E928666 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: Visser | Statement: [A. G. Visser, familyName, Visser]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Visser
Context triple: [A. G. Visser, familyName, Visser]
  • A. Visscher
    Visscher is a Dutch family name historically associated with prominent 17th-century mapmakers and printmakers from Amsterdam.
  • B. Viljoen
    Viljoen is an Afrikaans-origin surname commonly found in South Africa and Namibia, associated with several notable figures in politics, sports, and the military.
  • C. Jasaan
    Jasaan is a coastal municipality in Misamis Oriental, Philippines, known for its beaches, marine resources, and proximity to the urban center of Cagayan de Oro.
  • D. Kolderbos
    Kolderbos is a residential district of the Belgian city of Genk, known for its post-war social housing and multicultural community.
  • E. Vissering
    Vissering is a Dutch-origin surname borne by various individuals, including those of note in academic and professional fields.
  • 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: Visser
Triple: [A. G. Visser, familyName, Visser]
Generated description
Visser is a common Dutch surname borne by various notable individuals across fields such as sports, academia, and the arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Visser
Target entity description: Visser is a common Dutch surname borne by various notable individuals across fields such as sports, academia, and the arts.
  • A. Visscher
    Visscher is a Dutch family name historically associated with prominent 17th-century mapmakers and printmakers from Amsterdam.
  • B. Viljoen
    Viljoen is an Afrikaans-origin surname commonly found in South Africa and Namibia, associated with several notable figures in politics, sports, and the military.
  • C. Jasaan
    Jasaan is a coastal municipality in Misamis Oriental, Philippines, known for its beaches, marine resources, and proximity to the urban center of Cagayan de Oro.
  • D. Kolderbos
    Kolderbos is a residential district of the Belgian city of Genk, known for its post-war social housing and multicultural community.
  • E. Vissering
    Vissering is a Dutch-origin surname borne by various individuals, including those of note in academic and professional fields.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85a1ea00c8190b42cdc13a6bc61c3 completed April 10, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69e60451a89081909f9534fee6cb809f completed April 20, 2026, 10:47 a.m.
NEDg Description generation batch_69e610a5ea0481908169c58dc0831b76 completed April 20, 2026, 11:40 a.m.
NED2 Entity disambiguation (via description) batch_69e6182b06f88190ab36d976ac989019 completed April 20, 2026, 12:12 p.m.
Created at: April 8, 2026, 9:36 p.m.