Triple
T34476330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Zelig |
E885046
|
entity |
| Predicate | mediaFormatWithinStory |
P131
|
FINISHED |
| Object | 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: newsreel footage | Statement: [Leonard Zelig, mediaFormatWithinStory, newsreel footage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaFormatWithinStory Context triple: [Leonard Zelig, mediaFormatWithinStory, newsreel footage]
-
A.
mediaStandard
Indicates that something conforms to, is governed by, or is evaluated according to a particular media-related standard or specification.
-
B.
mediaType
chosen
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
C.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
D.
mediaResponse
Indicates that one entity serves as a reply or reaction in a media format (such as audio, video, or image) to another entity or communication.
-
E.
mediaGroupType
Indicates the classification or category of a media group based on its type or role.
- 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_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 1, 2026, 2:01 a.m.