Triple
T36489748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | recurrent neural networks |
E899021
|
entity |
| Predicate | canUseActivation |
P9928
|
FINISHED |
| Object | tanh |
—
|
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: tanh | Statement: [recurrent neural networks, canUseActivation, tanh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseActivation Context triple: [recurrent neural networks, canUseActivation, tanh]
-
A.
canBeActivatedFor
Indicates that one entity is capable of being put into an active or operational state by or for another entity.
-
B.
canUse
chosen
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
C.
canBeActivatedWithin
Indicates that one entity is capable of being activated or triggered within the spatial or temporal bounds defined by another entity.
-
D.
canEnable
Indicates that one entity has the capability or authority to activate, turn on, or make another entity or function operational.
-
E.
canBeUsed
Indicates that one entity is suitable or available to serve a particular function, purpose, or role in relation to another entity or 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:10 p.m.