Triple

T3584557
Position Surface form Disambiguated ID Type / Status
Subject Dan Laustsen E75880 entity
Predicate familyName P18 FINISHED
Object Laustsen
Laustsen is a Danish surname most notably associated with acclaimed cinematographer Dan Laustsen.
 E371872 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: Laustsen | Statement: [Dan Laustsen, familyName, Laustsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Laustsen
Context triple: [Dan Laustsen, familyName, Laustsen]
  • A. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • B. Knudstrup
    Knudstrup is a small locality in present-day Sweden historically notable as the birthplace of the astronomer Tycho Brahe.
  • C. Lindeberg
    Lindeberg is a surname most notably associated with the Finnish mathematician Jarl Waldemar Lindeberg, known for his contributions to probability theory and the central limit theorem.
  • D. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • E. Lönnbohm
    Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
  • 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: Laustsen
Triple: [Dan Laustsen, familyName, Laustsen]
Generated description
Laustsen is a Danish surname most notably associated with acclaimed cinematographer Dan Laustsen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Laustsen
Target entity description: Laustsen is a Danish surname most notably associated with acclaimed cinematographer Dan Laustsen.
  • A. Blomstedt
    Blomstedt is a surname most prominently associated with Herbert Blomstedt, a renowned Swedish conductor known for his interpretations of the classical and romantic repertoire.
  • B. Knudstrup
    Knudstrup is a small locality in present-day Sweden historically notable as the birthplace of the astronomer Tycho Brahe.
  • C. Lindeberg
    Lindeberg is a surname most notably associated with the Finnish mathematician Jarl Waldemar Lindeberg, known for his contributions to probability theory and the central limit theorem.
  • D. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • E. Lönnbohm
    Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
  • 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_69ad85d6dc3c8190b491b79b83e25461 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc10f9b508190bde4a4e4711dd452 completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b402f7ee6481908d06db05f9c09faf completed March 13, 2026, 12:28 p.m.
NEDg Description generation batch_69b403acc5e88190bc88bed8259393ba completed March 13, 2026, 12:31 p.m.
NED2 Entity disambiguation (via description) batch_69b40a7f82ac819099c2c324ebff76f7 completed March 13, 2026, 1 p.m.
Created at: March 8, 2026, 3:21 p.m.