Triple
T24652352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U2 |
E610285
|
entity |
| Predicate | usesVisualMediaFor |
P33573
|
FINISHED |
| Object | extending musical themes |
—
|
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: extending musical themes | Statement: [U2, usesVisualMediaFor, extending musical themes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVisualMediaFor Context triple: [U2, usesVisualMediaFor, extending musical themes]
-
A.
usesMusicVideo
Indicates that one entity incorporates or features another entity as a music video.
-
B.
mediaUse
chosen
Indicates that an entity makes use of, consumes, or engages with a particular medium or media resource.
-
C.
mediaDepictionAs
Indicates that one entity is portrayed or represented as another entity or in a particular way within some medium (e.g., image, film, text).
-
D.
visualTechnology
Indicates a relationship where one entity is a technology used to capture, process, display, or otherwise handle visual information for another entity or context.
-
E.
visualMedium
Indicates that one entity serves as the visual medium or format through which another entity is presented, communicated, or experienced.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 2:34 a.m.