Triple

T11638720
Position Surface form Disambiguated ID Type / Status
Subject George Neville E276596 entity
Predicate featuredInFormat P80112 FINISHED
Object silent black-and-white film LITERAL 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: silent black-and-white film | Statement: [George Neville, featuredInFormat, silent black-and-white film]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: featuredInFormat
Context triple: [George Neville, featuredInFormat, silent black-and-white film]
  • A. featuredIn
    Indicates that one entity appears or is prominently included within another entity, such as a person, work, or item being showcased in a larger work, event, or context.
  • B. featuredOn
    Indicates that one entity is prominently presented, highlighted, or showcased on or within another entity (such as a platform, publication, or product).
  • C. presentedIn
    Indicates that something is shown, displayed, or formally introduced within a particular context, medium, event, or setting.
  • D. featuredInDirector
    Indicates that an entity appears as a featured element within a director’s work, such as a film, show, or other directed production.
  • E. portrayalFormat chosen
    Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
  • F. None of above.

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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25e90c08190b7fb73939a2be3d7 completed April 10, 2026, 7:10 a.m.
PD Predicate disambiguation batch_69d85dd94bdc819091fa2ed33eb31624 completed April 10, 2026, 2:18 a.m.
Created at: April 8, 2026, 9:39 p.m.