Triple
T30382272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony E |
E772862
|
entity |
| Predicate | supportsFaceDetectionAF |
P187050
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sony E, supportsFaceDetectionAF, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFaceDetectionAF Context triple: [Sony E, supportsFaceDetectionAF, true]
-
A.
hasFaceDetectionAF
chosen
Indicates that an entity supports or uses autofocus functionality based on detecting human faces in the frame.
-
B.
hasAnimalDetectionAF
Indicates that an entity possesses or is associated with an animal-detection autofocus capability.
-
C.
hasFaceUnlock
Indicates that an entity supports or is equipped with a facial recognition–based unlocking feature.
-
D.
hasFaceLocation
Indicates that an entity has a specified position or region corresponding to a face within some spatial or visual context.
-
E.
supportsRealTimeEyeAF
Indicates that the subject provides real-time autofocus functionality specifically for tracking and focusing on a subject’s eyes.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8 p.m.