Triple
T27762390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Instance Normalization |
E701501
|
entity |
| Predicate | oftenReplaces |
P82114
|
FINISHED |
| Object | Batch Normalization in style transfer networks |
—
|
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: Batch Normalization in style transfer networks | Statement: [Instance Normalization, oftenReplaces, Batch Normalization in style transfer networks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenReplaces Context triple: [Instance Normalization, oftenReplaces, Batch Normalization in style transfer networks]
-
A.
oftenReplacedBy
chosen
Indicates that one entity is frequently substituted or superseded by another in similar contexts or uses.
-
B.
replacedFrequency
Indicates how often one entity is substituted for or takes the place of another over a given period.
-
C.
oftenFrom
Indicates that something frequently originates, derives, or comes from a particular source or location.
-
D.
replacedDuring
Indicates that one entity took the place of another entity during a specified time period or interval.
-
E.
primaryReplacementFor
Indicates that one entity serves as the main or preferred substitute or successor for another entity.
- 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 4:28 p.m.