Triple
T9497059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RRQ |
E229034
|
entity |
| Predicate | errorHandling |
P66396
|
FINISHED |
| Object | errors reported via TFTP ERROR messages |
—
|
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: errors reported via TFTP ERROR messages | Statement: [RRQ, errorHandling, errors reported via TFTP ERROR messages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorHandling Context triple: [RRQ, errorHandling, errors reported via TFTP ERROR messages]
-
A.
errorHandlingModel
Indicates how a system or component manages, responds to, and recovers from errors or exceptional conditions during operation.
-
B.
errorHandlingPattern
chosen
Indicates how errors are detected, propagated, and managed within a system or process.
-
C.
errorRecovery
Indicates that an entity detects a failure or error condition and initiates actions to restore normal or acceptable operation.
-
D.
errorPropagation
Indicates how an error in one component, process, or variable is transmitted to and affects other components, processes, or variables in a system.
-
E.
errorType
Indicates the specific category or kind of error associated with an event, action, or 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ecf4148190aa8f4733980166ae |
completed | April 1, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:56 p.m.