Triple

T9213351
Position Surface form Disambiguated ID Type / Status
Subject Mads Nipper E221179 entity
Predicate name P16 FINISHED
Object Mads Nipper E221179 NE FINISHED

How this triple was built (2 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: Mads Nipper | Statement: [Mads Nipper, name, Mads Nipper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mads Nipper
Context triple: [Mads Nipper, name, Mads Nipper]
  • A. Mads Nipper chosen
    Mads Nipper is a Danish business executive known for his leadership roles in major global companies and his advocacy for sustainable, purpose-driven business.
  • B. Jesper Nøhr
    Jesper Nøhr is a Danish software developer and entrepreneur best known for creating the code hosting platform Bitbucket.
  • C. Nicolaj Monberg
    Nicolaj Monberg is a film editor known for his work on the action thriller "Cold Pursuit."
  • D. Peter Aalbæk Jensen
    Peter Aalbæk Jensen is a Danish film producer and co-founder of the influential production company Zentropa, known for his collaborations with prominent directors such as Lars von Trier.
  • E. Christian Møller
    Christian Møller was a Danish theoretical physicist known for his contributions to quantum electrodynamics and the theory of relativity.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83eae42c8190a0ea9e040710a277 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda05406081909893bec3a092d3ce completed April 1, 2026, 8:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69d09ba1d3488190b2c999204f0d545b completed April 4, 2026, 5:03 a.m.
Created at: March 30, 2026, 7:27 p.m.