Triple

T12900852
Position Surface form Disambiguated ID Type / Status
Subject Lars Magne Ingebrigtsen E308605 entity
Predicate notableWork P4 FINISHED
Object Gnus E59588 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: Gnus | Statement: [Lars Magne Ingebrigtsen, notableWork, Gnus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gnus
Context triple: [Lars Magne Ingebrigtsen, notableWork, Gnus]
  • A. Gnus chosen
    Gnus is a flexible and extensible message reader for news and email, tightly integrated with the Emacs text editor.
  • B. MUTT
    MUTT is the common nickname for the M151 MUTT, a lightweight military utility vehicle used extensively by the U.S. armed forces during the Cold War era.
  • C. Postel
    Postel is a surname most prominently associated with Jon Postel, a pioneering computer scientist and key architect of the early Internet.
  • D. Groff
    Groff is a surname most prominently associated with American actor and singer Jonathan Groff, known for his work in musical theatre, television, and film.
  • E. GNU Emacs
    GNU Emacs is a highly extensible, customizable text editor and computing environment that serves as a flagship project of the GNU system and the free software movement.
  • 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97180ee708190b60a3e58c42f764f completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a56189b081909ed838addcb6d265 completed May 3, 2026, 1:31 a.m.
Created at: April 9, 2026, 5:40 p.m.