Triple
T30428699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iOS 11 |
E774099
|
entity |
| Predicate | targetedDeviceType |
P193309
|
FINISHED |
| Object | smartphone |
—
|
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: smartphone | Statement: [iOS 11, targetedDeviceType, smartphone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetedDeviceType Context triple: [iOS 11, targetedDeviceType, smartphone]
-
A.
targetedDevice
Indicates that one entity is the specific device toward which another entity’s action, effect, or configuration is directed.
-
B.
testedDeviceType
Indicates that one entity is the type or category of device on which another entity has been tested.
-
C.
intendedEquipmentType
Indicates that a particular piece of equipment is the planned or designated type to be used in a given context or activity.
-
D.
targetDeviceGeneration
Indicates the specific hardware or model generation of the device that is the focus or recipient of an action or relationship.
-
E.
storyDeviceType
Indicates the type or category of narrative device used within a story.
- 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: April 29, 2026, 8:06 p.m.