Triple

T18441844
Position Surface form Disambiguated ID Type / Status
Subject Lodewijk van Heiden E450547 entity
Predicate familyName P18 FINISHED
Object van Heiden
Van Heiden is a Dutch surname most notably associated with Admiral Lodewijk van Heiden, a distinguished naval officer in Russian service during the early 19th century.
 E1325734 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: van Heiden | Statement: [Lodewijk van Heiden, familyName, van Heiden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: van Heiden
Context triple: [Lodewijk van Heiden, familyName, van Heiden]
  • A. van der Heyden
    Van der Heyden is a Dutch-origin surname associated with various notable individuals in fields such as art, politics, and sports.
  • B. Verhaegen
    Verhaegen is a Dutch-language surname of Belgian and Dutch origin, borne by various notable figures in politics, academia, and the arts.
  • C. van Swanenburg
    Van Swanenburg is a Dutch family name historically associated with artists and notable figures from the Netherlands.
  • D. van Wijnbergen
    Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
  • E. Van der Madeweg
    Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit network.
  • 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: van Heiden
Triple: [Lodewijk van Heiden, familyName, van Heiden]
Generated description
Van Heiden is a Dutch surname most notably associated with Admiral Lodewijk van Heiden, a distinguished naval officer in Russian service during the early 19th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: van Heiden
Target entity description: Van Heiden is a Dutch surname most notably associated with Admiral Lodewijk van Heiden, a distinguished naval officer in Russian service during the early 19th century.
  • A. van der Heyden
    Van der Heyden is a Dutch-origin surname associated with various notable individuals in fields such as art, politics, and sports.
  • B. Verhaegen
    Verhaegen is a Dutch-language surname of Belgian and Dutch origin, borne by various notable figures in politics, academia, and the arts.
  • C. van Swanenburg
    Van Swanenburg is a Dutch family name historically associated with artists and notable figures from the Netherlands.
  • D. van Wijnbergen
    Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
  • E. Van der Madeweg
    Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit network.
  • 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_69d8d381d6388190a9e94e9c658174e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e51c11b1288190b9ed4497751197d1 completed April 19, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a040fdb4c648190aa56212c3c1e15ce completed May 13, 2026, 5:44 a.m.
NEDg Description generation batch_6a0418c2621481909497c663272f5407 completed May 13, 2026, 6:22 a.m.
NED2 Entity disambiguation (via description) batch_6a041bca3d688190972d5c0d5bba70ed completed May 13, 2026, 6:35 a.m.
Created at: April 10, 2026, 11:30 a.m.