Triple
T7000216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Q-in-Q |
E162316
|
entity |
| Predicate | encapsulationDepth |
P33248
|
FINISHED |
| Object | double VLAN tagging |
—
|
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: double VLAN tagging | Statement: [Q-in-Q, encapsulationDepth, double VLAN tagging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encapsulationDepth Context triple: [Q-in-Q, encapsulationDepth, double VLAN tagging]
-
A.
encapsulation
chosen
Indicates that one entity encloses, contains, or wraps another entity or set of details within a defined boundary, often hiding internal structure from external access.
-
B.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
C.
testDepth
Indicates that an entity is evaluated or measured based on how deep or thorough it is, often in terms of levels, layers, or extent below a surface or baseline.
-
D.
hasDepth
Indicates that an entity possesses a measurable extent or distance from its surface inward or from top to bottom.
-
E.
depthMetresApprox
Indicates an approximate measurement of how deep something is in metres, rather than an exact value.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc0e54c88190b092870f2d128510 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.