Triple
T28615603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LineTo |
E724265
|
entity |
| Predicate | errorRetrieval |
P164926
|
FINISHED |
| Object | GetLastError |
—
|
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: GetLastError | Statement: [LineTo, errorRetrieval, GetLastError]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorRetrieval Context triple: [LineTo, errorRetrieval, GetLastError]
-
A.
errorDescription
Indicates a textual explanation that describes the nature or details of an error that has occurred.
-
B.
errorRecovery
Indicates that an entity detects a failure or error condition and initiates actions to restore normal or acceptable operation.
-
C.
errorType
Indicates the specific category or kind of error associated with an event, action, or entity.
-
D.
errorModel
Indicates the specific model or framework used to represent, quantify, or simulate errors in a process, system, or prediction.
-
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. 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f652a3a8208190a4fdd66f34138bd2 |
completed | May 2, 2026, 7:38 p.m. |
Created at: April 28, 2026, 4:31 a.m.