Triple
T36933768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Pro (11-inch, 1st generation) |
E913554
|
entity |
| Predicate | bezelCharacteristic |
P48670
|
FINISHED |
| Object | narrow uniform bezels |
—
|
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: narrow uniform bezels | Statement: [iPad Pro (11-inch, 1st generation), bezelCharacteristic, narrow uniform bezels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bezelCharacteristic Context triple: [iPad Pro (11-inch, 1st generation), bezelCharacteristic, narrow uniform bezels]
-
A.
bezelType
chosen
Indicates the style or design of the bezel associated with an object or device.
-
B.
bezelFunction
Indicates the functional role or purpose that a bezel serves in relation to another object or system.
-
C.
beltMaterial
Indicates the material from which a belt is made.
-
D.
beltFeature
Indicates that an entity possesses or is characterized by a specific belt-related attribute or component.
-
E.
beltDesign
Indicates a relationship where one entity specifies or defines the design, style, or pattern applied to a belt.
- 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_69f76e896c988190880c130e01303dd4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fdf2dc148190bca1bf6bca2e6732 |
completed | May 5, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.