Triple
T26563945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott C3a (block format) |
E666325
|
entity |
| Predicate | errorDescription |
P161035
|
FINISHED |
| Object | airplane vignette printed upside down relative to frame |
—
|
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: airplane vignette printed upside down relative to frame | Statement: [Scott C3a (block format), errorDescription, airplane vignette printed upside down relative to frame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: errorDescription Context triple: [Scott C3a (block format), errorDescription, airplane vignette printed upside down relative to frame]
-
A.
errorType
Indicates the specific category or kind of error associated with an event, action, or entity.
-
B.
reasonForException
Indicates the specific cause or justification for why a normal rule, process, or condition does not apply in a given case.
-
C.
errorModel
Indicates the specific model or framework used to represent, quantify, or simulate errors in a process, system, or prediction.
-
D.
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.
-
E.
errorSide
Indicates the side, party, or component on which an error occurs or is attributed in a given 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_69ee9cf7e94481909f0d556b36e43572 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6149cc0c88190aadaacfa45a2382e |
completed | May 2, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60f24ed608190bffe6c6084fc2f7a |
completed | May 2, 2026, 2:50 p.m. |
Created at: April 27, 2026, 1:54 a.m.