Triple
T27762403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Instance Normalization |
E701501
|
entity |
| Predicate | epsilonRole |
P163555
|
FINISHED |
| Object | numerical stability in variance normalization |
—
|
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: numerical stability in variance normalization | Statement: [Instance Normalization, epsilonRole, numerical stability in variance normalization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epsilonRole Context triple: [Instance Normalization, epsilonRole, numerical stability in variance normalization]
-
A.
encodingRole
Indicates the role or function an entity has in the process of encoding information into a particular form or representation.
-
B.
gammaRole
Indicates a tertiary or supporting role that an entity plays within a structured hierarchy of roles or participants in an event or relationship.
-
C.
eraRole
Indicates the specific role, function, or capacity an entity has within a particular historical or temporal era.
-
D.
effectiveRole
Indicates the functional role or capacity an entity actually performs or holds in a given context, regardless of its formal or nominal designation.
-
E.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
- 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6397b64f881909d811225e57aac5e |
completed | May 2, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f63893cc188190883ac9321a95d2dc |
completed | May 2, 2026, 5:46 p.m. |
Created at: April 27, 2026, 4:28 p.m.