Triple
T1907595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CentOS |
E38036
|
entity |
| Predicate | stabilityFocus |
P31957
|
FINISHED |
| Object | high stability and long-term 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: high stability and long-term support | Statement: [CentOS, stabilityFocus, high stability and long-term support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stabilityFocus Context triple: [CentOS, stabilityFocus, high stability and long-term support]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
stabilizedBy
Indicates that an entity’s state, structure, or behavior is made more steady, secure, or resistant to change through the influence or support of another entity.
-
C.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
stabilityGoal
chosen
Indicates a relationship where an action, policy, or entity is aimed at achieving, maintaining, or enhancing stability in a given system or context.
-
E.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafeba3d88190afcce67483d8625b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.