Triple
T20120948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Decontamination chambers (film) |
E490604
|
entity |
| Predicate | cameraFocusOn |
P130176
|
FINISHED |
| Object | shower and cleansing sequence |
—
|
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: shower and cleansing sequence | Statement: [Decontamination chambers (film), cameraFocusOn, shower and cleansing sequence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraFocusOn Context triple: [Decontamination chambers (film), cameraFocusOn, shower and cleansing sequence]
-
A.
sceneCenter
chosen
Indicates that one entity serves as the central or focal point of a scene in relation to another entity.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
D.
mapsFocus
Indicates that one entity serves as the primary subject, area, or aspect of attention, emphasis, or concentration for another entity.
-
E.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6673e79dc81908fbd387c067fce79 |
completed | April 20, 2026, 5:49 p.m. |
| PD | Predicate disambiguation | batch_69e54cf788188190a46cc49c9ce7617f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:30 p.m.