Triple
T5497943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smart Keyboard |
E144255
|
entity |
| Predicate | hasBacklighting |
P12005
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Smart Keyboard, hasBacklighting, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBacklighting Context triple: [Smart Keyboard, hasBacklighting, no]
-
A.
usesBacklightTechnology
Indicates that one entity employs backlight technology to illuminate or enhance the visibility of another entity or its display.
-
B.
hasBacklitKeyboard
chosen
Indicates that an entity is equipped with a keyboard that includes built-in lighting behind the keys.
-
C.
hasOnboardLEDs
Indicates that one entity is equipped with built-in LED lights as part of its hardware.
-
D.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
E.
lightingCharacteristic
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
- 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_69c008f5a2748190bce7a39aabf87a6d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f08c2a4819093e772a1497c7ecc |
completed | March 22, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69c01b052f3c81909f71c6add0f35a6f |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:32 p.m.