Triple
T442015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTV |
E10132
|
entity |
| Predicate | logoFeatures |
P10231
|
FINISHED |
| Object | stylized block letter M with graffiti-style TV |
—
|
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: stylized block letter M with graffiti-style TV | Statement: [MTV, logoFeatures, stylized block letter M with graffiti-style TV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: logoFeatures Context triple: [MTV, logoFeatures, stylized block letter M with graffiti-style TV]
-
A.
logoFeature
chosen
Indicates that an entity serves as a distinctive visual element or component within a logo.
-
B.
logoDescription
Indicates a textual description that explains the appearance, style, or content of a logo.
-
C.
logoImage
Indicates the image that serves as the logo representing an entity.
-
D.
logoDerivedFrom
Indicates that one logo is created, adapted, or otherwise based on another logo as its source or inspiration.
-
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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef42b4008190abed9d79926c7022 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2edde2b9c8190bd20b582eb4c5065 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.