Triple
T30382451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon RF lens mount |
E772866
|
entity |
| Predicate | sensorFormatSupport |
P170212
|
FINISHED |
| Object | 35 mm 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: 35 mm full-frame | Statement: [Canon RF lens mount, sensorFormatSupport, 35 mm full-frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensorFormatSupport Context triple: [Canon RF lens mount, sensorFormatSupport, 35 mm full-frame]
-
A.
sensorFormat
Indicates the data encoding or representation standard used by a sensor to output its measurements.
-
B.
usedOnSensorFormats
Indicates that something (such as a method, algorithm, or configuration) is applied to or compatible with specific sensor data formats.
-
C.
detectorFormat
Indicates the specific data or signal representation used by a detector to encode or output its measurements.
-
D.
supportsRasterFormat
Indicates that one entity is capable of handling, processing, or outputting data in a specified raster image format.
-
E.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
- 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_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 8:01 p.m.