Triple

T1143979
Position Surface form Disambiguated ID Type / Status
Subject Max Havelaar E23520 entity
Predicate hasCharacter P2308 FINISHED
Object 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.
 E131051 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: Sjaalman | Statement: [Max Havelaar, hasCharacter, Sjaalman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sjaalman
Context triple: [Max Havelaar, hasCharacter, Sjaalman]
  • A. Neeleman
    Neeleman is a surname most notably associated with David Neeleman, the Brazilian-American entrepreneur and founder of multiple airlines including JetBlue Airways.
  • B. Aeltge Velthuys
    Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
  • C. Benschop
    Benschop is a small village in the Dutch province of Utrecht, known for its rural character and traditional polder landscape.
  • D. Willem
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • E. Michiel
    Michiel is a Dutch given name most famously borne by the 17th-century admiral Michiel de Ruyter.
  • 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: Sjaalman
Triple: [Max Havelaar, hasCharacter, Sjaalman]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sjaalman
Target entity description: 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.
  • A. Neeleman
    Neeleman is a surname most notably associated with David Neeleman, the Brazilian-American entrepreneur and founder of multiple airlines including JetBlue Airways.
  • B. Aeltge Velthuys
    Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
  • C. Benschop
    Benschop is a small village in the Dutch province of Utrecht, known for its rural character and traditional polder landscape.
  • D. Willem
    Willem is a given name, primarily used in Dutch-speaking regions, that corresponds to the English name William.
  • E. Michiel
    Michiel is a Dutch given name most famously borne by the 17th-century admiral Michiel de Ruyter.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc5008d8819095c1ffb5db5b4911 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac59b31ed08190a1647af9af1f2648 completed March 7, 2026, 5 p.m.
NEDg Description generation batch_69ac5a38ebb0819091cb81e23770ae50 completed March 7, 2026, 5:02 p.m.
NED2 Entity disambiguation (via description) batch_69ac5aa2ad188190b4c6a29e3c2c8d79 completed March 7, 2026, 5:04 p.m.
Created at: March 1, 2026, 7:44 p.m.