Triple
T18204853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLM-R |
E435876
|
entity |
| Predicate | hasEncoderLayersApprox |
P48113
|
FINISHED |
| Object | 12 (base variant) |
—
|
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: 12 (base variant) | Statement: [XLM-R, hasEncoderLayersApprox, 12 (base variant)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEncoderLayersApprox Context triple: [XLM-R, hasEncoderLayersApprox, 12 (base variant)]
-
A.
hasNumberOfWeightLayers
chosen
Indicates the relationship that specifies how many distinct weight layers are present in a given model or structure.
-
B.
usesFullyConnectedLayersAtEnd
Indicates that the model’s architecture concludes with one or more fully connected (dense) layers applied after preceding layers or modules.
-
C.
inceptionApproximation
Indicates an approximate or estimated starting point or origin of something, rather than an exact inception time.
-
D.
hasApproximateNumberOfSymbols
Indicates that an entity is associated with a quantity of symbols that is approximate rather than exact.
-
E.
hasNeuralNetwork
Indicates that an entity possesses, incorporates, or is equipped with a neural network.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.