Triple
T2382360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille |
E46337
|
entity |
| Predicate | controlLayout |
P38398
|
FINISHED |
| Object | multiple volume and tone controls |
—
|
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: multiple volume and tone controls | Statement: [Lucille, controlLayout, multiple volume and tone controls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlLayout Context triple: [Lucille, controlLayout, multiple volume and tone controls]
-
A.
exportControl
Indicates that an entity is subject to rules or restrictions governing the transfer or export of goods, services, or information across borders.
-
B.
canControl
Indicates that one entity has the ability or authority to direct, manage, or influence the behavior or state of another entity.
-
C.
areaCControl
Indicates that an entity exercises control or authority over a specific geographic area or region.
-
D.
controlSurfaces
Indicates that one entity functions as a control surface or set of control surfaces used to influence, steer, or regulate the behavior or state of another entity.
-
E.
areaAControl
Indicates that one entity exercises control or authority over a specified area or region.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7b98c988190abdb4fe51bf65bde |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:57 p.m.