Triple
T2114660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasson Jeans |
E42578
|
entity |
| Predicate | mediumOfAdvertising |
P5765
|
FINISHED |
| Object | television commercials |
—
|
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: television commercials | Statement: [Sasson Jeans, mediumOfAdvertising, television commercials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumOfAdvertising Context triple: [Sasson Jeans, mediumOfAdvertising, television commercials]
-
A.
mediaEnvironment
Indicates the surrounding media or contextual setting in which an entity exists, operates, or is presented.
-
B.
secondaryMedium
Indicates that an entity is associated with an additional, non-primary medium or channel through which it is expressed, delivered, or communicated.
-
C.
commonMedium
Indicates that two or more entities share the same medium or channel through which interaction, communication, or transmission occurs.
-
D.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
-
E.
primaryMedium
chosen
Indicates the main material, format, or channel through which something is created, expressed, or communicated.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0724e08190a0a4210d86261d6d |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7ba08948190a3c236bb53ee4257 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.