Triple
T2979436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IEEE 802.3an-2006 |
E80474
|
entity |
| Predicate | usesNumberOfPairs |
P42152
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [IEEE 802.3an-2006, usesNumberOfPairs, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNumberOfPairs Context triple: [IEEE 802.3an-2006, usesNumberOfPairs, 4]
-
A.
usesPairsForTransmit
Indicates that an entity performs transmission by utilizing paired elements (such as wires, channels, or signals) as the medium or mechanism for sending information or energy.
-
B.
usesPairsForReceive
Indicates that an entity performs its receiving operation by using paired elements or resources as the basis for that reception.
-
C.
numberOfCounts
chosen
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
dualPair
Indicates that two entities form a dual pair, standing in a mathematically defined dual relationship where each is the dual counterpart of the other.
-
E.
canHavePairingSymmetry
Indicates that an entity is capable of exhibiting or supporting a specific type of pairing symmetry in its interactions or internal structure.
- 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_69ad8b15f6ac8190be5fd16a33edcb4f |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad999cca40819082e2d6d10bdb7872 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.