Triple
T29392037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPI |
E745388
|
entity |
| Predicate | signalRole_SS |
P168760
|
FINISHED |
| Object | slave select line |
—
|
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: slave select line | Statement: [SPI, signalRole_SS, slave select line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: signalRole_SS Context triple: [SPI, signalRole_SS, slave select line]
-
A.
signalType
Indicates the specific kind or category of signal associated with or used by an entity or interaction.
-
B.
signalProperty
Indicates that one entity has a specific characteristic, attribute, or feature related to a signal.
-
C.
signalRole_MOSI
Indicates that one entity functions as a signal or communication role specifically associated with the MOSI (Master Out Slave In) line in a signaling or communication context.
-
D.
signalReception
Indicates the reception or detection of a transmitted signal by a receiving entity.
-
E.
signalLevel
Indicates the intensity or strength of a transmitted or received signal in a communication context.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f67805551c81909e016ae9e3031076 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f675ff62c48190a634bbb8896973b9 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676f73c3481909f01fa69851b7298 |
completed | May 2, 2026, 10:13 p.m. |
Created at: April 28, 2026, 2:43 p.m.