Triple
T26242959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris visual processor |
E656363
|
entity |
| Predicate | appliesToDeviceType |
P44687
|
FINISHED |
| Object | smartphones |
—
|
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: smartphones | Statement: [Iris visual processor, appliesToDeviceType, smartphones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToDeviceType Context triple: [Iris visual processor, appliesToDeviceType, smartphones]
-
A.
appliesToProductType
chosen
Indicates that something (such as a rule, offer, or condition) is relevant or applicable specifically to a certain type or category of product.
-
B.
testedDeviceType
Indicates that one entity is the type or category of device on which another entity has been tested.
-
C.
targetedDevice
Indicates that one entity is the specific device toward which another entity’s action, effect, or configuration is directed.
-
D.
includesDevices
Indicates that one entity contains, encompasses, or has as part of it one or more devices.
-
E.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
- 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_69ee5b4c59a881909d9ee4fd013fffd5 |
completed | April 26, 2026, 6:37 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 26, 2026, 9:04 p.m.