Triple

T13056492
Position Surface form Disambiguated ID Type / Status
Subject Hubert Laws E327588 entity
Predicate givenName P17 FINISHED
Object Hubert E164283 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: Hubert | Statement: [Hubert Laws, givenName, Hubert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hubert
Context triple: [Hubert Laws, givenName, Hubert]
  • A. Hubert chosen
    Hubert is a masculine given name of Germanic origin meaning "bright heart" or "shining intellect," historically borne by saints, nobles, and notable public figures.
  • B. Roger Hubert
    Roger Hubert was a French cinematographer known for his work on mid-20th-century films, contributing to the visual style of classic French cinema.
  • C. Thomas Hubert
    Thomas Hubert is an author known for his work on the artificial intelligence program AlphaGo Zero.
  • D. Hubert Hawkins
    Hubert Hawkins is the bumbling yet brave entertainer-turned-hero portrayed by Danny Kaye in the 1955 musical comedy film "The Court Jester."
  • E. Hubert Hudson
    Hubert Hudson was a British navigator and seaman best known for serving under Sir Ernest Shackleton during the ill-fated Imperial Trans-Antarctic Expedition.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980bd305c8190bcf191b2d35ec8de completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbdead348190aa7aaa29c371d72a completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:58 p.m.