Triple
T30644168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EOS M6 Mark II |
E780072
|
entity |
| Predicate | flashMount |
P57768
|
FINISHED |
| Object | standard hot shoe |
—
|
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: standard hot shoe | Statement: [Canon EOS M6 Mark II, flashMount, standard hot shoe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flashMount Context triple: [Canon EOS M6 Mark II, flashMount, standard hot shoe]
-
A.
mountingInterface
chosen
Indicates that one entity serves as the surface, structure, or connection point onto which another entity is mounted or attached.
-
B.
mountType
Indicates the manner or configuration in which one object is mounted or attached to another.
-
C.
runnerMounting
Indicates a relationship where a runner is being attached, installed, or positioned onto another object or surface.
-
D.
mountSystem
Indicates attaching a filesystem or storage resource to a system so that it becomes accessible for use.
-
E.
trainMounting
Indicates a relationship where an entity is boarding or getting onto a train.
- F. None of above.
Provenance (3 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a58cd808190bc1cdaa106291084 |
completed | May 2, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:29 p.m.