Triple
T2998379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 10BASE5 |
E81124
|
entity |
| Predicate | maximumRepeaterCount |
P18344
|
FINISHED |
| Object | 4 repeaters between two stations (typical 802.3 rule) |
—
|
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 repeaters between two stations (typical 802.3 rule) | Statement: [10BASE5, maximumRepeaterCount, 4 repeaters between two stations (typical 802.3 rule)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumRepeaterCount Context triple: [10BASE5, maximumRepeaterCount, 4 repeaters between two stations (typical 802.3 rule)]
-
A.
maximumRepeaters
chosen
Indicates the greatest number of repeaters that are allowed or observed within a given system, connection, or configuration.
-
B.
repetitionCount
Indicates the number of times a particular event, action, or pattern is repeated within a given context.
-
C.
maximumConsecutiveTerms
Indicates the greatest number of terms that can occur in an unbroken, continuous sequence within a given context or structure.
-
D.
maximumNumberOfSegments
Indicates the greatest allowable or observed count of discrete segments into which something can be or is divided.
-
E.
maximumNumber
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f766408190a5591efce8346bb9 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.