Triple
T8610133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gentoo ebuild repository |
E203894
|
entity |
| Predicate | mirroredAt |
P83865
|
FINISHED |
| Object | rsync.gentoo.org |
—
|
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: rsync.gentoo.org | Statement: [Gentoo ebuild repository, mirroredAt, rsync.gentoo.org]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mirroredAt Context triple: [Gentoo ebuild repository, mirroredAt, rsync.gentoo.org]
-
A.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
B.
primaryMirrorShape
Indicates that one entity has a primary mirror whose geometric shape or curvature type is specified by the other entity.
-
C.
hasSecondaryMirrorPosition
Indicates the spatial placement or configuration of a secondary mirror relative to the primary optical system.
-
D.
mirrorCount
Indicates the number of mirrors associated with or present in relation to a given entity or context.
-
E.
primaryMirrorArea
Indicates the surface area of the primary mirror involved in the optical or reflective system.
- F. None of above. chosen
Provenance (4 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ee96ac8190809817c403da2889 |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc455437488190b7506f820daf6e32 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:25 p.m.