Triple

T15625652
Position Surface form Disambiguated ID Type / Status
Subject Dirty Grandpa E375668 entity
Predicate productionCompany P490 FINISHED
Object QED International E199732 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: QED International | Statement: [Dirty Grandpa, productionCompany, QED International]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: QED International
Context triple: [Dirty Grandpa, productionCompany, QED International]
  • A. QED International chosen
    QED International is an independent film production and financing company known for backing a range of commercially oriented feature films.
  • B. J. Muller International
    J. Muller International is an engineering and design firm known for its work on major infrastructure projects, including long-span bridges such as the Confederation Bridge in Canada.
  • C. Quark, Inc.
    Quark, Inc. is a software company best known for creating the professional desktop publishing application QuarkXPress.
  • D. Reed International
    Reed International was a major British publishing and media conglomerate that became one of the world’s largest magazine and information services groups before merging into Reed Elsevier (now RELX).
  • E. Leaf International
    Leaf International was a confectionery company known for producing candies and chewing gum before being acquired by Cloetta.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f415c2c81909e232e1c6531da93 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.