Triple

T4101113
Position Surface form Disambiguated ID Type / Status
Subject Mudbound E87941 entity
Predicate productionCompany P490 FINISHED
Object Macro Media E322229 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: Macro Media | Statement: [Mudbound, productionCompany, Macro Media]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macro Media
Context triple: [Mudbound, productionCompany, Macro Media]
  • A. Macro Media chosen
    Macro Media is a film and television production company known for backing culturally resonant, character-driven projects such as the 2016 drama "Fences."
  • B. Macromedia
    Macromedia was a pioneering software company best known for creating web and multimedia tools like Flash and Dreamweaver before being acquired by Adobe.
  • C. Viacom
    Viacom is a major American media conglomerate known for its extensive portfolio of television networks, film production, and entertainment brands.
  • D. Metromedia
    Metromedia was a major American media company that owned a group of independent television and radio stations, many of which later formed the core of the Fox Broadcasting Company.
  • E. Obvious Corporation
    Obvious Corporation was the early holding company and development vehicle created by Twitter’s founders that incubated and spun out Twitter as an independent company.
  • 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_69aed94564cc8190a9c1457daedb6e7f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefd0ed168819093c83ba079d6725c completed March 9, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b7833b081909bf5a87ee709b49f completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:40 p.m.