Triple
T15131810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Active Edge |
E361437
|
entity |
| Predicate | targetedUseCase |
P57747
|
FINISHED |
| Object | hands-on quick access to assistant |
—
|
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: hands-on quick access to assistant | Statement: [Active Edge, targetedUseCase, hands-on quick access to assistant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetedUseCase Context triple: [Active Edge, targetedUseCase, hands-on quick access to assistant]
-
A.
targetsUseCase
chosen
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
B.
usesTarget
Indicates that one entity employs, applies, or operates on another entity as its target or object of action.
-
C.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
hasUseCase
Indicates that one entity is employed, applied, or utilized as a solution or method to address a particular need, problem, or scenario associated with another entity.
-
E.
partOfUse
Indicates that something functions as a component or constituent within the use or application of something else.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b194748190801e3956bf2429d4 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:06 a.m.