Triple
T8650093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Air (M2, 2022) |
E205076
|
entity |
| Predicate | keyboardFeature |
P84135
|
FINISHED |
| Object | backlit keys |
—
|
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: backlit keys | Statement: [MacBook Air (M2, 2022), keyboardFeature, backlit keys]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: keyboardFeature Context triple: [MacBook Air (M2, 2022), keyboardFeature, backlit keys]
-
A.
keyHitter
Indicates that an entity is a powerful or highly effective performer, especially in a competitive or performance-based context.
-
B.
keyAction
Indicates an action that is performed using a key, typically involving locking, unlocking, or otherwise operating a mechanism that requires a key.
-
C.
keyboardShortcut
Indicates that one entity is a keyboard key combination used to trigger or activate the function, command, or action represented by another entity.
-
D.
hasKeyboard
Indicates that one entity possesses or is equipped with a keyboard as a component or accessory.
-
E.
keyLayout
Indicates the specific spatial arrangement and organization of keys or buttons within an input device or interface.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4813d0548190b203e594acc38c8f |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc473e44988190a3b02498e5fff668 |
completed | March 31, 2026, 10:14 p.m. |
Created at: March 30, 2026, 6:29 p.m.