Triple
T1775271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Air (M1, 2020) |
E38962
|
entity |
| Predicate | supportsTrueTone |
P203
|
FINISHED |
| Object | True Tone |
—
|
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: True Tone | Statement: [MacBook Air (M1, 2020), supportsTrueTone, True Tone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTrueTone Context triple: [MacBook Air (M1, 2020), supportsTrueTone, True Tone]
-
A.
hasAlwaysOnDisplay
Indicates that an entity features an always-on display capability that remains visible without fully waking the device.
-
B.
supportsDisplayPortAltMode
Indicates that one entity is capable of transmitting video and audio using the DisplayPort Alternate Mode over a USB-C or similar connection to another entity.
-
C.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
D.
supportsView
Indicates that one entity provides the capability to display, render, or present another entity in a particular view or format.
-
E.
supportsProduct
Indicates that one entity provides assistance, compatibility, or necessary resources for the operation, use, or maintenance of a specified product.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab17e368048190b7b73d156400f772 |
completed | March 6, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69aa61cd4c1c8190a8dff391f5642bfe |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.