Triple
T25310838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MAC-in-MAC |
E634602
|
entity |
| Predicate | addsHeaderType |
P158375
|
FINISHED |
| Object | backbone MAC header |
—
|
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: backbone MAC header | Statement: [MAC-in-MAC, addsHeaderType, backbone MAC header]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsHeaderType Context triple: [MAC-in-MAC, addsHeaderType, backbone MAC header]
-
A.
addsContentType
Indicates that one entity augments or associates another entity with a specific content type.
-
B.
belongsToHeader
Indicates that something is associated with, contained within, or conceptually grouped under a specific header.
-
C.
addsCardType
Indicates that one entity introduces or associates a specific card type with another entity or collection.
-
D.
addsFeatureType
Indicates that one entity introduces or incorporates a specific feature type into another entity or system.
-
E.
registerType
Indicates that an entity is classified or recorded under a specific type or category within a registration 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_69e75a972c6481909bc11710e8d30a6c |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4939e84dc8190bef761d9bfee08a6 |
completed | May 1, 2026, 11:50 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:26 p.m.