Triple

T14072331
Position Surface form Disambiguated ID Type / Status
Subject Johannes Bogerman E338640 entity
Predicate familyName P18 FINISHED
Object Bogerman
Bogerman is a Dutch surname most notably associated with Johannes Bogerman, a prominent 17th-century Reformed theologian and church leader.
 E1077429 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: Bogerman | Statement: [Johannes Bogerman, familyName, Bogerman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bogerman
Context triple: [Johannes Bogerman, familyName, Bogerman]
  • A. Veit
    Veit is a German surname most notably associated with the 19th-century Romantic painter Philipp Veit.
  • B. Bomer
    Bomer is the surname of American actor Matt Bomer, known for his roles in television and film such as "White Collar" and "The Normal Heart."
  • C. Blixem
    Blixem is an alternative name for Blitzen, one of Santa Claus’s traditional flying reindeer known from the Christmas poem “A Visit from St. Nicholas.”
  • D. Rygge
    Rygge is a municipality in southeastern Norway, historically known for its military air station and proximity to the town of Moss.
  • E. Emmerich
    Emmerich is the German form of the given name Imre, used primarily in German-speaking regions.
  • 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: Bogerman
Triple: [Johannes Bogerman, familyName, Bogerman]
Generated description
Bogerman is a Dutch surname most notably associated with Johannes Bogerman, a prominent 17th-century Reformed theologian and church leader.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bogerman
Target entity description: Bogerman is a Dutch surname most notably associated with Johannes Bogerman, a prominent 17th-century Reformed theologian and church leader.
  • A. Veit
    Veit is a German surname most notably associated with the 19th-century Romantic painter Philipp Veit.
  • B. Bomer
    Bomer is the surname of American actor Matt Bomer, known for his roles in television and film such as "White Collar" and "The Normal Heart."
  • C. Blixem
    Blixem is an alternative name for Blitzen, one of Santa Claus’s traditional flying reindeer known from the Christmas poem “A Visit from St. Nicholas.”
  • D. Rygge
    Rygge is a municipality in southeastern Norway, historically known for its military air station and proximity to the town of Moss.
  • E. Emmerich
    Emmerich is the German form of the given name Imre, used primarily in German-speaking regions.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5aa828819098ef55a70a0decbc completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb66eeb248190b73e992ab6b9af82 completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc37502048190b24438c0fb161fdf completed May 7, 2026, 4:53 p.m.
NED2 Entity disambiguation (via description) batch_69fcc3db83ac819083b728d039b8d345 completed May 7, 2026, 4:54 p.m.
Created at: April 9, 2026, 10:21 p.m.