Triple
T35123143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | …sofferte onde serene… |
E1014219
|
entity |
| Predicate | hasElectronicComponent |
P156609
|
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: […sofferte onde serene…, hasElectronicComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectronicComponent Context triple: […sofferte onde serene…, hasElectronicComponent, yes]
-
A.
hasElectronicsFeature
Indicates that an entity possesses or is characterized by a specific electronic-related feature or capability.
-
B.
electronicComponents
chosen
Indicates a relationship where one entity consists of, contains, or is associated with specific electronic components.
-
C.
hardwareComponent
Indicates that one entity is a physical hardware part or module that is contained in, attached to, or functionally part of another hardware system or device.
-
D.
isMechanicalOrElectronic
Indicates that something operates using mechanical components, electronic components, or a combination of both.
-
E.
hasElectronicEffect
Indicates that one entity exerts or contributes an electronic influence or effect on another entity within a specified context.
- 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_69f76dd8b6948190aaa32b081816bd94 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:01 p.m.