Triple
T22411995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ImageNet Classification with Deep Convolutional Neural Networks |
E554013
|
entity |
| Predicate | top5ErrorRateOnILSVRC2012 |
P48403
|
FINISHED |
| Object | 15.3% |
—
|
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: 15.3% | Statement: [ImageNet Classification with Deep Convolutional Neural Networks, top5ErrorRateOnILSVRC2012, 15.3%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: top5ErrorRateOnILSVRC2012 Context triple: [ImageNet Classification with Deep Convolutional Neural Networks, top5ErrorRateOnILSVRC2012, 15.3%]
-
A.
top5ErrorRate
chosen
Indicates the proportion of instances where the correct answer is not among the top five predicted results.
-
B.
inceptionApproximation
Indicates an approximate or estimated starting point or origin of something, rather than an exact inception time.
-
C.
pretrainedOn
Indicates that a model has been trained in advance using a specified dataset or data source before being applied to downstream tasks.
-
D.
graph500Rank
Indicates the position or standing of an entity within the Graph500 benchmark ranking.
-
E.
targetBitErrorRate
Indicates the specified or required bit error rate that a communication system aims to achieve or not exceed as a performance target.
- 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15943dd84819099e77563da470594 |
completed | April 29, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:46 p.m.