Triple
T6797354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DY |
E156089
|
entity |
| Predicate | operatorBusinessModel |
P6233
|
FINISHED |
| Object | low-cost model |
—
|
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: low-cost model | Statement: [DY, operatorBusinessModel, low-cost model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatorBusinessModel Context triple: [DY, operatorBusinessModel, low-cost model]
-
A.
operatingModel
Indicates how an organization structures and manages its processes, resources, and governance to deliver its products or services.
-
B.
usesBusinessModel
chosen
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
C.
commercialOperator
Indicates that an entity operates or manages a commercial activity, service, or facility, typically for profit or business purposes.
-
D.
businessModelFocus
Indicates that one entity’s business model is centered on, tailored to, or primarily oriented around another entity or specific focus area.
-
E.
formerBusinessModel
Indicates that an entity previously operated under a particular business model, but no longer does so.
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ca0c288190a990180fb7cfd08f |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.