Triple
T30644147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EOS M6 Mark II |
E780072
|
entity |
| Predicate | faceDetection |
P25983
|
FINISHED |
| Object | supported |
—
|
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: supported | Statement: [Canon EOS M6 Mark II, faceDetection, supported]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceDetection Context triple: [Canon EOS M6 Mark II, faceDetection, supported]
-
A.
facesChallenge
Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
-
B.
faceVisibility
Indicates that one entity’s face is visible to another entity or from a particular viewpoint.
-
C.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
D.
visualFeature
chosen
Indicates a relationship where one entity possesses or exhibits a particular visual characteristic or attribute of another entity.
-
E.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
- 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_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:29 p.m.