Triple

T8956214
Position Surface form Disambiguated ID Type / Status
Subject Secretary-General of the International Maritime Organization E213476 entity
Predicate officeHeldBy P537 FINISHED
Object Ove Nielsen E65667 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: Ove Nielsen | Statement: [Secretary-General of the International Maritime Organization, officeHeldBy, Ove Nielsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ove Nielsen
Context triple: [Secretary-General of the International Maritime Organization, officeHeldBy, Ove Nielsen]
  • A. Ove Nielsen chosen
    Ove Nielsen was a Danish maritime administrator who became the inaugural Secretary-General of the International Maritime Organization, helping to shape the early framework of global maritime regulation.
  • B. Ole Henriksen
    Ole Henriksen is a Danish skincare expert and entrepreneur best known for founding his eponymous skincare brand and popularizing spa-inspired, glow-focused beauty products.
  • C. Rolf Nilsen
    Rolf Nilsen is a businessman best known as the owner of the Ontario Hockey League’s Flint Firebirds.
  • D. Rob Nielsen
    Rob Nielsen is an individual known primarily as the child of Erik Nielsen.
  • E. Henrik Christensen
    Henrik Christensen is a prominent robotics researcher and academic known for his influential contributions to computer vision, autonomous systems, and robotics education.
  • 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_69ca8399ad2081909f8fa41d4314c215 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6728965881908e9f14aaee0c5a18 completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc216ff2c819098056dff0de9479f completed April 3, 2026, 1:35 p.m.
Created at: March 30, 2026, 7 p.m.