Triple
T14510102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viva Bahriya |
E340372
|
entity |
| Predicate | lifestylePositioning |
P97831
|
FINISHED |
| Object | family-friendly living |
—
|
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: family-friendly living | Statement: [Viva Bahriya, lifestylePositioning, family-friendly living]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lifestylePositioning Context triple: [Viva Bahriya, lifestylePositioning, family-friendly living]
-
A.
lifestyleFeature
chosen
Indicates that one entity offers, includes, or is characterized by a particular lifestyle-related amenity, attribute, or quality for another entity.
-
B.
lifestyle
Indicates that an entity’s way of living or habitual behaviors are associated with, influence, or characterize another entity or outcome.
-
C.
supportsLifestyle
Indicates that one entity provides the resources, conditions, or assistance necessary for another entity to maintain a particular way of living.
-
D.
brandPositioning
Indicates how a brand is strategically placed and perceived in the minds of its target audience relative to competitors.
-
E.
stylePositioning
Indicates how an entity is spatially or visually arranged or aligned relative to a reference frame or other elements.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e5b7b48190878be271840c265b |
completed | April 14, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:21 a.m.