Triple
T30357893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony A-mount |
E772195
|
entity |
| Predicate | usedOnSensorFormats |
P169095
|
FINISHED |
| Object | full-frame |
—
|
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: full-frame | Statement: [Sony A-mount, usedOnSensorFormats, full-frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnSensorFormats Context triple: [Sony A-mount, usedOnSensorFormats, full-frame]
-
A.
sensorFormat
Indicates the data encoding or representation standard used by a sensor to output its measurements.
-
B.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
usedInFormat
Indicates that something (such as a method, standard, or component) is employed or applied within a particular format.
-
D.
usedFormat
Indicates that one entity employs or applies a particular format or representation in relation to another entity.
-
E.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
- 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_69f6823fe8c48190a8911627f79dd949 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f679496c188190ba585792f987a1f4 |
completed | May 2, 2026, 10:23 p.m. |
Created at: April 29, 2026, 7:57 p.m.