Triple

T10162362
Position Surface form Disambiguated ID Type / Status
Subject The Scientific Basis E233920 entity
Predicate hasEditor P1954 FINISHED
Object P. J. van der Linden
P. J. van der Linden is an editor known for work on scientific publications, including the volume titled "The Scientific Basis."
 E845585 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: P. J. van der Linden | Statement: [The Scientific Basis, hasEditor, P. J. van der Linden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: P. J. van der Linden
Context triple: [The Scientific Basis, hasEditor, P. J. van der Linden]
  • A. Jan van der Linden
    Jan van der Linden was an architect known for his role in designing Los Angeles’ historic Union Station.
  • B. Peter Oskam
    Peter Oskam is a Dutch politician and former judge who has served as mayor of Capelle aan den IJssel.
  • C. Dirk Margadant
    Dirk Margadant was a Dutch architect known for designing prominent public buildings in the Netherlands, including notable railway stations.
  • D. Pieter R. de Jong
    Pieter R. de Jong is a Dutch professional who studied at Utrecht University and is recognized as a notable alumnus for his contributions in his field.
  • E. C. M. van den Heever
    C. M. van den Heever was a prominent Afrikaans poet, novelist, and critic associated with the influential Dertigers literary movement in South Africa.
  • 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: P. J. van der Linden
Triple: [The Scientific Basis, hasEditor, P. J. van der Linden]
Generated description
P. J. van der Linden is an editor known for work on scientific publications, including the volume titled "The Scientific Basis."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: P. J. van der Linden
Target entity description: P. J. van der Linden is an editor known for work on scientific publications, including the volume titled "The Scientific Basis."
  • A. Jan van der Linden
    Jan van der Linden was an architect known for his role in designing Los Angeles’ historic Union Station.
  • B. Peter Oskam
    Peter Oskam is a Dutch politician and former judge who has served as mayor of Capelle aan den IJssel.
  • C. Dirk Margadant
    Dirk Margadant was a Dutch architect known for designing prominent public buildings in the Netherlands, including notable railway stations.
  • D. Pieter R. de Jong
    Pieter R. de Jong is a Dutch professional who studied at Utrecht University and is recognized as a notable alumnus for his contributions in his field.
  • E. C. M. van den Heever
    C. M. van den Heever was a prominent Afrikaans poet, novelist, and critic associated with the influential Dertigers literary movement in South Africa.
  • 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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec5b5194819095645e9174897b0f completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300cc37dc8190b331c8d205f40284 completed April 6, 2026, 12:39 a.m.
NEDg Description generation batch_69d30254aabc8190966a4398c59a851e completed April 6, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69d30305924c8190998cbefa372dca9a completed April 6, 2026, 12:49 a.m.
Created at: March 30, 2026, 9:09 p.m.