Triple
T1636249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Hat Enterprise Linux |
E35364
|
entity |
| Predicate | supportModel |
P936
|
FINISHED |
| Object | commercial support |
—
|
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: commercial support | Statement: [Red Hat Enterprise Linux, supportModel, commercial support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportModel Context triple: [Red Hat Enterprise Linux, supportModel, commercial support]
-
A.
support
Indicates that one entity provides assistance, endorsement, or backing to another entity or its actions.
-
B.
supportBase
Indicates that one entity serves as a foundational or backing structure that physically or functionally supports another entity.
-
C.
typeOfSupport
chosen
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
D.
supportColor
Indicates that an entity is compatible with, or can be rendered or displayed using, a specified color.
-
E.
providesSupportTo
Indicates that one entity offers help, resources, or reinforcement to another entity to aid its function, stability, or success.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907cac610819083cafd4396b6d66c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.