Triple
T30774091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-H2 |
E783609
|
entity |
| Predicate | filmSimulationModes |
P170800
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fujifilm X-H2, filmSimulationModes, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmSimulationModes Context triple: [Fujifilm X-H2, filmSimulationModes, yes]
-
A.
filmSetting
Indicates the place, time, or environment in which the events of a film are set or take place.
-
B.
exposureModes
Indicates the different ways or conditions under which an entity can be exposed to another entity, factor, or influence.
-
C.
filmingTechnique
Indicates the specific method or style used to capture visual content during the filming process.
-
D.
studioSystemFilm
Indicates that a film was produced, distributed, or otherwise created under the control or framework of a particular studio system.
-
E.
filmAbility
Indicates that one entity has the capability or skill to create, direct, or otherwise produce films involving another entity.
- 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_69f224b1519081908b9db003fd2073e0 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:40 p.m.