Triple
T2108429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 10BASE-T |
E42447
|
entity |
| Predicate | pairUsage |
P4791
|
FINISHED |
| Object | two pairs used |
—
|
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: two pairs used | Statement: [10BASE-T, pairUsage, two pairs used]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pairUsage Context triple: [10BASE-T, pairUsage, two pairs used]
-
A.
pairBond
Indicates a long-term, typically exclusive social or reproductive partnership formed between two individuals.
-
B.
parityWith
Indicates that two entities share the same parity, such as both being even or both being odd.
-
C.
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.
-
D.
usedWith
chosen
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbae03f308190841f5a419bb821f6 |
completed | March 7, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69abb7b7b6288190afa11b4d93bd5666 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.