Triple
T8414337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MVME147 |
E198696
|
entity |
| Predicate | hasWatchdogTimer |
P60696
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [MVME147, hasWatchdogTimer, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWatchdogTimer Context triple: [MVME147, hasWatchdogTimer, yes]
-
A.
hasTimer
chosen
Indicates that an entity is associated with or controlled by a timer mechanism that measures or limits a duration or interval.
-
B.
hasClock
Indicates that one entity possesses, contains, or is equipped with a clock.
-
C.
hasTimingCapability
Indicates that an entity possesses the ability to measure, control, or manage timing-related aspects of an operation or process.
-
D.
hasTimeIndication
Indicates that something includes, specifies, or is associated with a particular time-related indication (such as a timestamp, time period, or temporal marker).
-
E.
hasTypicalUseTime
Indicates the usual or expected duration or time period during which something is commonly used or in operation.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e328cc8190b3b038005d0bb66f |
completed | March 31, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69cb70d473dc8190af8ea81ee5aa970d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.