Triple
T9317783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α9 series |
E224166
|
entity |
| Predicate | shutterType |
P88057
|
FINISHED |
| Object | electronic shutter support |
—
|
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: electronic shutter support | Statement: [Sony α9 series, shutterType, electronic shutter support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shutterType Context triple: [Sony α9 series, shutterType, electronic shutter support]
-
A.
shellType
Indicates the type or classification of a shell associated with an entity (e.g., its form, structure, or category).
-
B.
doorType
Indicates the specific kind or category of door associated with an entity.
-
C.
hingeType
Indicates the specific kind or configuration of hinge mechanism that connects two parts or surfaces.
-
D.
typeOfChamber
Indicates the specific kind or category of chamber that an entity belongs to or is classified as.
-
E.
shotType
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd358b66148190a918c107490c8406 |
completed | April 1, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:38 p.m.