Triple
T5910836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Krizhevsky |
E131452
|
entity |
| Predicate | algorithmicContribution |
P11773
|
FINISHED |
| Object | ReLU activation in large-scale CNNs |
—
|
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: ReLU activation in large-scale CNNs | Statement: [Alex Krizhevsky, algorithmicContribution, ReLU activation in large-scale CNNs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: algorithmicContribution Context triple: [Alex Krizhevsky, algorithmicContribution, ReLU activation in large-scale CNNs]
-
A.
relatedAlgorithm
Indicates that one algorithm has a meaningful connection or association with another algorithm, such as similarity, dependency, or complementary function.
-
B.
algorithmDesigner
Indicates that one entity is responsible for creating or designing algorithms used by another entity or within a particular system.
-
C.
algorithmType
Indicates the specific kind or category of algorithm associated with an entity or process.
-
D.
notableContribution
Indicates that an entity has made a significant, recognized contribution to another entity, field, work, or endeavor.
-
E.
researchContribution
chosen
Indicates that an entity has produced or participated in creating new knowledge, findings, or innovations within a research context.
- 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c048fc112c8190b905bf561c9de096 |
completed | March 22, 2026, 7:54 p.m. |
| PD | Predicate disambiguation | batch_69c03352208c8190968efed05a9fd416 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.