Triple
T10185922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maestro |
E236906
|
entity |
| Predicate | targetEndUsers |
P481
|
FINISHED |
| Object | consumers |
—
|
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: consumers | Statement: [Maestro, targetEndUsers, consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetEndUsers Context triple: [Maestro, targetEndUsers, consumers]
-
A.
targetMarket
chosen
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
targetDevelopers
Indicates that something is specifically aimed at, intended for, or directed toward developers as its primary audience or users.
-
C.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded36e9808190b385c5aec4889e00 |
completed | April 2, 2026, 4:14 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:12 p.m.