Triple
T30357889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony A-mount |
E772195
|
entity |
| Predicate | supportsAutofocusLenses |
P207237
|
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: [Sony A-mount, supportsAutofocusLenses, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAutofocusLenses Context triple: [Sony A-mount, supportsAutofocusLenses, 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.
supportsInterchangeableLenses
Indicates that one entity is capable of using or accommodating different lenses that can be removed and replaced interchangeably.
-
C.
hasDigitalFocus
Indicates that an entity is primarily oriented toward or centered on digital technologies, channels, or activities.
-
D.
poseFocus
Indicates that attention or emphasis is directed toward a particular pose or body position within a scene or interaction.
-
E.
autofocusDetectionRange
Indicates the distance range within which an autofocus system can reliably detect and lock focus on a subject.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 7:57 p.m.