Triple
T18204299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DistilBERT |
E435865
|
entity |
| Predicate | numberOfAttentionHeads |
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: [DistilBERT, numberOfAttentionHeads, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAttentionHeads Context triple: [DistilBERT, numberOfAttentionHeads, 12]
-
A.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
B.
hasCanonicalNumberOfHeads
Indicates that an entity possesses the standard or officially recognized number of heads for its kind.
-
C.
hasNumberOfWeightLayers
Indicates the relationship that specifies how many distinct weight layers are present in a given model or structure.
-
D.
numberOfAttributes
Indicates the total count of distinct attributes or properties associated with a given entity or object.
-
E.
numberOfColossalHeads
Indicates the quantity of colossal heads associated with or attributed to a given subject.
- 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_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. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.