Triple
T30382279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony E |
E772862
|
entity |
| Predicate | hasNativeLensesFrom |
P195355
|
FINISHED |
| Object | Sony |
—
|
NE NERFINISHED |
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: Sony | Statement: [Sony E, hasNativeLensesFrom, Sony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNativeLensesFrom Context triple: [Sony E, hasNativeLensesFrom, Sony]
-
A.
usesAsLens
Indicates that one entity employs another entity as a lens or optical element through which to view, focus, or modify light or images.
-
B.
hasMirrorOrLensMaterial
Indicates that an object’s mirror or lens component is made from a specified material.
-
C.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
D.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
E.
supportsInterchangeableLenses
Indicates that one entity is capable of using or accommodating different lenses that can be removed and replaced interchangeably.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69fdbc5da9988190b95234bce4cc2062 |
completed | May 8, 2026, 10:35 a.m. |
Created at: April 29, 2026, 8 p.m.