Triple
T28506545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debian package archive |
E721377
|
entity |
| Predicate | mirrorCountApprox |
P8981
|
FINISHED |
| Object | hundreds of mirrors worldwide |
—
|
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: hundreds of mirrors worldwide | Statement: [Debian package archive, mirrorCountApprox, hundreds of mirrors worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mirrorCountApprox Context triple: [Debian package archive, mirrorCountApprox, hundreds of mirrors worldwide]
-
A.
mirrorCount
chosen
Indicates the number of mirrors associated with or present in relation to a given entity or context.
-
B.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
C.
hasApproximateNumberOfMiniatures
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
D.
mirroredOn
Indicates that one entity is a reflective counterpart of another, such that its structure, appearance, or configuration is reversed or symmetrically aligned relative to the other.
-
E.
mineCountApproximate
Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
- 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_69f01a5c072081908c7b04bcf6478da9 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 3:09 a.m.