Triple
T18724382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BERT_BASE |
E457858
|
entity |
| Predicate | numAttentionHeads |
P130209
|
FINISHED |
| Object | 12 |
—
|
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 | Statement: [BERT_BASE, numAttentionHeads, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numAttentionHeads Context triple: [BERT_BASE, numAttentionHeads, 12]
-
A.
numberOfAttentionHeads
chosen
Indicates the number of distinct attention heads used within an attention mechanism or layer in a model.
-
B.
usesSelfAttention
Indicates that an entity employs a self-attention mechanism to compute representations by relating each part of its input to all other parts.
-
C.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
D.
hiddenSize
Indicates the size or dimensionality of the internal representation used within a model or component that is not directly exposed as output.
-
E.
hasCanonicalNumberOfHeads
Indicates that an entity possesses the standard or officially recognized number of heads for its kind.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56abcfc048190a01dee959e768768 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.