Triple

T28454856
Position Surface form Disambiguated ID Type / Status
Subject The Knockout E716681 entity
Predicate hasCinematography P1953 FINISHED
Object Frank D. Williams NE NERFINISHED

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: Frank D. Williams | Statement: [The Knockout, hasCinematography, Frank D. Williams]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCinematography
Context triple: [The Knockout, hasCinematography, Frank D. Williams]
  • A. hasCinematicFeature
    Indicates that something possesses a specific cinematic characteristic, quality, or element related to film or visual storytelling.
  • B. cinematographyNotedFor
    Indicates that the subject’s cinematography is especially recognized or distinguished for the object (such as a particular work, style, or notable quality).
  • C. cinematographyBy chosen
    Indicates that the cinematographic work (such as the camera work or visual style of a film or video) is created or supervised by a specified person or entity.
  • D. cinematographyIncludes
    Indicates that a cinematographic work or process contains or makes use of specific visual techniques, elements, or components as part of its overall execution.
  • E. cinematographyAwardedTo
    Indicates that a cinematography-related award has been given to a particular recipient (such as a person or team) for their work.
  • 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_69efd6b76f8c8190a7ba908aca280942 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f6bbf6e33c819086e5176d64e7a614 completed May 3, 2026, 3:07 a.m.
PD Predicate disambiguation batch_69f6ba6b1e6c8190adf9d6a257e0b744 completed May 3, 2026, 3 a.m.
Created at: April 28, 2026, 1:53 a.m.