Triple
T7980145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PixelSense |
E185549
|
entity |
| Predicate | brandingRegion |
P80120
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [PixelSense, brandingRegion, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandingRegion Context triple: [PixelSense, brandingRegion, global]
-
A.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
B.
brandingNote
Indicates that an entity has an associated note or comment specifically about its branding, such as style, usage, or presentation guidelines.
-
C.
hasTourismRegionBrand
Indicates that an entity is associated with or belongs to a specific tourism region brand used for destination marketing or regional tourism identity.
-
D.
brandingStyle
Indicates the specific visual and stylistic approach used to represent a brand’s identity.
-
E.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
- F. None of above. chosen
Provenance (4 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c261904819086910898071f3629 |
completed | March 31, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69cb048009a08190b4c577208a9f8f76 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:14 p.m.