Triple
T15593429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia N78 |
E374806
|
entity |
| Predicate | cameraAutofocus |
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 N78, cameraAutofocus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraAutofocus Context triple: [Nokia N78, cameraAutofocus, 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.
typicalBackFocus
Indicates a relationship where attention, emphasis, or focus is characteristically directed toward the back or rear part of something.
-
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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5e43d48190a8fd367f13f1c7e1 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:12 a.m.