Triple
T22975492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPod "Silhouettes" campaign |
E571304
|
entity |
| Predicate | supportsBrandMessage |
P91438
|
FINISHED |
| Object | "1,000 songs in your pocket" |
—
|
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: "1,000 songs in your pocket" | Statement: [iPod "Silhouettes" campaign, supportsBrandMessage, "1,000 songs in your pocket"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsBrandMessage Context triple: [iPod "Silhouettes" campaign, supportsBrandMessage, "1,000 songs in your pocket"]
-
A.
supportsBrand
chosen
Indicates that one entity endorses, promotes, or is compatible with a particular brand.
-
B.
supportsProduct
Indicates that one entity provides assistance, compatibility, or necessary resources for the operation, use, or maintenance of a specified product.
-
C.
supportsContentBrands
Indicates that one entity provides functionality, compatibility, or infrastructure necessary for the operation or distribution of specific content brands.
-
D.
compatibleBrand
Indicates that one brand is suitable for use with, or functions properly alongside, another brand.
-
E.
exportBrand
Indicates a relationship where a brand is sold or distributed outside its home market into foreign or international markets.
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18235de508190ab9675d005870ff6 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:48 p.m.