Triple
T28583959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timeout Detection and Recovery |
E723442
|
entity |
| Predicate | relatedErrorMessage |
P161035
|
FINISHED |
| Object | Display driver stopped responding and has recovered |
—
|
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: Display driver stopped responding and has recovered | Statement: [Timeout Detection and Recovery, relatedErrorMessage, Display driver stopped responding and has recovered]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedErrorMessage Context triple: [Timeout Detection and Recovery, relatedErrorMessage, Display driver stopped responding and has recovered]
-
A.
errorDescription
chosen
Indicates a textual explanation that describes the nature or details of an error that has occurred.
-
B.
associatedFault
Indicates a relationship where a given entity is linked to, or occurs in connection with, a specific fault or error condition.
-
C.
reasonForException
Indicates the specific cause or justification for why a normal rule, process, or condition does not apply in a given case.
-
D.
relatedMessageType
Indicates that one message is associated with another by specifying the type or category of that related message.
-
E.
errorTerm
Indicates the specific discrepancy or residual value that quantifies the difference between an observed outcome and its predicted or true value in a model or calculation.
- 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_69f01d7f92e481909847f5f3f3174a89 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a002e71bdc48190b922f2d3b362d259 |
completed | May 10, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_6a002e1a28708190b65f9e657c770bab |
completed | May 10, 2026, 7:04 a.m. |
Created at: April 28, 2026, 4:16 a.m.