Triple

T17096416
Position Surface form Disambiguated ID Type / Status
Subject Javanese literature E414861 entity
Predicate documentedBy P4310 FINISHED
Object Zoetmulder
Zoetmulder was a prominent scholar and philologist renowned for his pioneering research and comprehensive documentation of Old Javanese language and literature.
 E1250106 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: Zoetmulder | Statement: [Javanese literature, documentedBy, Zoetmulder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zoetmulder
Context triple: [Javanese literature, documentedBy, Zoetmulder]
  • A. Molenaar
    Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
  • B. Goudriaan
    Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • C. Beerzelberg
    Beerzelberg is a modest hill in Belgium known as the highest natural point in Antwerp Province.
  • D. Lovaart
    Lovaart is a canalized waterway in western Belgium that serves as a branch of the Yser River, used primarily for drainage and local navigation.
  • E. 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.
  • 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: Zoetmulder
Triple: [Javanese literature, documentedBy, Zoetmulder]
Generated description
Zoetmulder was a prominent scholar and philologist renowned for his pioneering research and comprehensive documentation of Old Javanese language and literature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zoetmulder
Target entity description: Zoetmulder was a prominent scholar and philologist renowned for his pioneering research and comprehensive documentation of Old Javanese language and literature.
  • A. Molenaar
    Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
  • B. Goudriaan
    Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
  • C. Beerzelberg
    Beerzelberg is a modest hill in Belgium known as the highest natural point in Antwerp Province.
  • D. Lovaart
    Lovaart is a canalized waterway in western Belgium that serves as a branch of the Yser River, used primarily for drainage and local navigation.
  • E. 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.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbfdc9c88190b4e75bbdf4105c1e completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012eedfd7c8190b267dedd403f5f2b completed May 11, 2026, 1:20 a.m.
NEDg Description generation batch_6a01302666a48190b7d7c33306e63911 completed May 11, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_6a01308426a48190882dd057126bc43a completed May 11, 2026, 1:27 a.m.
Created at: April 10, 2026, 5:35 a.m.