Triple
T474491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinetoscope |
E9030
|
entity |
| Predicate | exhibitedContentType |
P640
|
FINISHED |
| Object | actualities |
—
|
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: actualities | Statement: [Kinetoscope, exhibitedContentType, actualities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exhibitedContentType Context triple: [Kinetoscope, exhibitedContentType, actualities]
-
A.
hasExhibitFormat
Indicates the specific format or medium in which an exhibit is presented or made available.
-
B.
hasContentType
chosen
Indicates that an entity is associated with or classified by a specific type of content.
-
C.
exhibitionType
Indicates the specific category or kind of exhibition associated with an entity (e.g., art show, trade fair, scientific exhibit).
-
D.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
E.
canExhibit
Indicates that one entity has the ability or potential to display, manifest, or show a particular property, behavior, or characteristic.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f039f3d88190a7c93ecbf1bf5f58 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.