Triple
T7665277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adapter |
E173608
|
entity |
| Predicate | objectAdapterUses |
P39741
|
FINISHED |
| Object | Object composition |
—
|
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: Object composition | Statement: [Adapter, objectAdapterUses, Object composition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: objectAdapterUses Context triple: [Adapter, objectAdapterUses, Object composition]
-
A.
adaptsFrom
Indicates that one entity is derived, modified, or transformed from another, preserving core elements while changing form, medium, or context.
-
B.
usedInAdaptation
Indicates that something (such as a character, plot element, or work) is incorporated or appears within an adaptation of another original source.
-
C.
hasAdapter
chosen
Indicates that one entity includes, uses, or is equipped with an adapter component that enables compatibility or connection with another system or interface.
-
D.
useOfModel
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
E.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4 p.m.