Triple
T18016404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SqueezeNet |
E431007
|
entity |
| Predicate | parameterCountRelativeTo |
P129421
|
FINISHED |
| Object | 50x fewer parameters than AlexNet |
—
|
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: 50x fewer parameters than AlexNet | Statement: [SqueezeNet, parameterCountRelativeTo, 50x fewer parameters than AlexNet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parameterCountRelativeTo Context triple: [SqueezeNet, parameterCountRelativeTo, 50x fewer parameters than AlexNet]
-
A.
parameterCount
Indicates the number of parameters associated with a given function, method, or callable entity.
-
B.
argumentCount
Indicates the number of arguments that a function, method, or callable entity takes.
-
C.
numberOfParametersOfLargestVariant
Indicates the total count of parameters in the variant that has the greatest number of parameters among all variants of an entity.
-
D.
prologueCount
Indicates the number of prologues associated with a given work or entity.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:24 a.m.