Triple
T9025833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Retina |
E216044
|
entity |
| Predicate | usedInDeviceCategory |
P31538
|
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: [Retina, usedInDeviceCategory, smartphones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInDeviceCategory Context triple: [Retina, usedInDeviceCategory, smartphones]
-
A.
usedInDeviceFamily
chosen
Indicates that something (such as a component, technology, or feature) is employed or incorporated within a particular family of related devices.
-
B.
supportsDeviceCategory
Indicates that one entity is compatible with and can operate or accommodate a specified category of devices.
-
C.
usesDevice
Indicates that one entity operates, employs, or relies on a particular device to perform an action or achieve a purpose.
-
D.
includesDevices
Indicates that one entity contains, encompasses, or has as part of it one or more devices.
-
E.
categoryIUsedFor
Indicates that one entity is used as a category or classification label for another entity.
- 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_69ca83a5fa88819088144801b4dd7245 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6a7ce71c81908041814dc9ec1713 |
completed | April 1, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee132f08190940749c7c522e4c1 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:07 p.m.