Triple
T30428116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EF-M lens mount |
E774088
|
entity |
| Predicate | adapterName |
P172179
|
FINISHED |
| Object | Canon Mount Adapter EF-EOS M |
—
|
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: Canon Mount Adapter EF-EOS M | Statement: [Canon EF-M lens mount, adapterName, Canon Mount Adapter EF-EOS M]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adapterName Context triple: [Canon EF-M lens mount, adapterName, Canon Mount Adapter EF-EOS M]
-
A.
deviceName
Indicates that a device is associated with a specific name or label used to identify it.
-
B.
chipSetName
Indicates the specific chipset designation or model name associated with a hardware component or device.
-
C.
connectorTypeDesignation
Indicates the specific type or classification assigned to a connector within a connection or interface relationship.
-
D.
connectorType
Indicates the specific kind or category of connection interface that links two entities.
-
E.
chassisName
Indicates the designated name or identifier assigned to a chassis in a system or dataset.
- 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a915ead881909463ae46419c343e |
completed | May 3, 2026, 1:47 a.m. |
Created at: April 29, 2026, 8:06 p.m.