Triple
T14906083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia N93 |
E360133
|
entity |
| Predicate | mainCameraAutofocus |
P85619
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Nokia N93, mainCameraAutofocus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCameraAutofocus Context triple: [Nokia N93, mainCameraAutofocus, yes]
-
A.
autofocusPoints
Indicates the relationship between a camera (or imaging device) and the specific focus points it can automatically select or use for focusing.
-
B.
autofocusSystem
chosen
Indicates that there is an autofocus mechanism or method used to automatically adjust focus in an imaging or optical system.
-
C.
hasDigitalFocus
Indicates that an entity is primarily oriented toward or centered on digital technologies, channels, or activities.
-
D.
supportsCameraControl
Indicates that one entity provides functionality for another entity to remotely manage or adjust camera settings or operations.
-
E.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded60cd5588190b1efecc2b220da69 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:12 a.m.