Triple
T34476367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Zelig |
E885047
|
entity |
| Predicate | featuredInStyle |
P121907
|
FINISHED |
| Object | black-and-white newsreel footage |
—
|
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: black-and-white newsreel footage | Statement: [Leonard Zelig, featuredInStyle, black-and-white newsreel footage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuredInStyle Context triple: [Leonard Zelig, featuredInStyle, black-and-white newsreel footage]
-
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.
inTheStyleOf
chosen
Indicates that one entity is created, performed, or presented in a manner that imitates or closely resembles the characteristic style of another entity.
-
D.
featuredFor
Indicates that one entity is highlighted, promoted, or specially showcased in the context or for the benefit of another entity.
-
E.
featuredOnFormat
Indicates that something is prominently presented or highlighted within a particular medium, channel, or content format.
- 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_69f349c880408190ade571c471ab154a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a033029023481909d9fa4a76b954879 |
completed | May 12, 2026, 1:50 p.m. |
| PD | Predicate disambiguation | batch_6a032d9f1fa48190bd1c94a8f930d02c |
completed | May 12, 2026, 1:39 p.m. |
Created at: May 1, 2026, 2:01 a.m.