Triple

T6701969
Position Surface form Disambiguated ID Type / Status
Subject Marius Borg Høiby E152901 entity
Predicate givenName P17 FINISHED
Object Marius E141117 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: Marius | Statement: [Marius Borg Høiby, givenName, Marius]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marius
Context triple: [Marius Borg Høiby, givenName, Marius]
  • A. Marius chosen
    Marius is the given name of the Norwegian mathematician Sophus Lie, a pioneer in the theory of continuous transformation groups (Lie groups).
  • B. Marius
    Marius was a short-lived 3rd-century Roman usurper who briefly ruled the breakaway Gallic Empire during the Crisis of the Third Century.
  • C. Marius
    Marius is a French film adaptation of Marcel Pagnol’s classic Marseille-set play, brought to the screen under the direction of actor-filmmaker Daniel Auteuil.
  • D. Marius
    Marius is the family name (nomen) of the prominent Roman general and statesman Gaius Marius, known for his military reforms and multiple consulships in the late Roman Republic.
  • E. Marius Pontmercy
    Marius Pontmercy is a central character in Victor Hugo’s novel *Les Misérables*, a young idealistic law student and revolutionary who falls in love with Cosette.
  • 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_69c68807adbc8190b8632df42b39eda0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d0e5eb0c81908c4fa3febd2d23ca completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70083e1948190b5ee3fffb9783531 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:06 p.m.