Triple
T30811325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-H2S |
E784651
|
entity |
| Predicate | autofocusFeatures |
P85619
|
FINISHED |
| Object | subject detection AF |
—
|
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: subject detection AF | Statement: [Fujifilm X-H2S, autofocusFeatures, subject detection AF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: autofocusFeatures Context triple: [Fujifilm X-H2S, autofocusFeatures, subject detection AF]
-
A.
autofocusCoverage
Indicates the extent or area within a frame over which a camera’s autofocus system can actively detect and focus on subjects.
-
B.
focusFeature
Indicates that one entity is the primary or emphasized feature, aspect, or attribute being highlighted or concentrated on in relation to another.
-
C.
autofocusPoints
Indicates the relationship between a camera (or imaging device) and the specific focus points it can automatically select or use for focusing.
-
D.
autofocusSystem
chosen
Indicates that there is an autofocus mechanism or method used to automatically adjust focus in an imaging or optical system.
-
E.
accessibilityFeatures
Indicates the specific tools, settings, or design elements provided to make something usable or understandable for people with disabilities or diverse access needs.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:43 p.m.