Triple
T3787240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIL-STD-1553 databus |
E85556
|
entity |
| Predicate | maximumRemoteTerminals |
P32169
|
FINISHED |
| Object | 31 |
—
|
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: 31 | Statement: [MIL-STD-1553 databus, maximumRemoteTerminals, 31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumRemoteTerminals Context triple: [MIL-STD-1553 databus, maximumRemoteTerminals, 31]
-
A.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
B.
maximumDevicesPerChannel
chosen
Indicates the highest number of devices that are allowed to be associated with or operate on a single channel.
-
C.
maximumService
Indicates that an entity provides the highest allowable or achievable level of service within a given context or system.
-
D.
maximumTermCount
Indicates the highest number of terms that are allowed or considered within a given context or operation.
-
E.
terminalNumber
Indicates the specific terminal identifier associated with an entity, such as a device, port, or connection point, within a larger system or network.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:13 p.m.