Triple
T300084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple M1 |
E6177
|
entity |
| Predicate | targetDeviceType |
P4634
|
FINISHED |
| Object | desktop computer |
—
|
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: desktop computer | Statement: [Apple M1, targetDeviceType, desktop computer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDeviceType Context triple: [Apple M1, targetDeviceType, desktop computer]
-
A.
definesDeviceType
chosen
Indicates that one entity specifies or assigns the device type classification of another entity.
-
B.
deviceIndicates
Indicates that a device provides a signal, status, or output that conveys information about a condition, event, or state.
-
C.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
D.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
-
E.
supportsDeviceCount
Indicates the number of devices that a system, service, or component is capable of supporting concurrently.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.