Triple
T307987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy of Television Arts & Sciences |
E6343
|
entity |
| Predicate | logoUsed |
P4845
|
FINISHED |
| Object | Television Academy logo |
—
|
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 Academy logo | Statement: [Academy of Television Arts & Sciences, logoUsed, Television Academy logo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: logoUsed Context triple: [Academy of Television Arts & Sciences, logoUsed, Television Academy logo]
-
A.
logoFeature
Indicates that an entity serves as a distinctive visual element or component within a logo.
-
B.
logoImage
chosen
Indicates the image that serves as the logo representing an entity.
-
C.
logoDerivedFrom
Indicates that one logo is created, adapted, or otherwise based on another logo as its source or inspiration.
-
D.
logoDescription
Indicates a textual description that explains the appearance, style, or content of a logo.
-
E.
brandImage
Indicates the perceived overall impression, reputation, and associations that people hold about a particular brand.
- 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_69a2e79230508190b912ecb555aae17e |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea3289608190a36c20a47761c6e4 |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93f38308190b4b480c951f1a1c3 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.