Triple
T17521113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soft Actor-Critic |
E426679
|
entity |
| Predicate | policyUpdateBasedOn |
P127770
|
FINISHED |
| Object | reparameterization trick |
—
|
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: reparameterization trick | Statement: [Soft Actor-Critic, policyUpdateBasedOn, reparameterization trick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyUpdateBasedOn Context triple: [Soft Actor-Critic, policyUpdateBasedOn, reparameterization trick]
-
A.
policySetBy
Indicates that a particular policy is established, defined, or determined by a specific entity or authority.
-
B.
policyBasis
Indicates that one entity serves as the foundational rationale, authority, or guiding principle upon which a policy or rule is established or justified.
-
C.
advancesPolicyOf
Indicates that one entity actively promotes, supports, or furthers the policy objectives or agenda of another entity.
-
D.
policyShift
Indicates a change or adjustment in an existing policy, typically reflecting a new direction, priority, or approach.
-
E.
policyVariation
Indicates that one policy differs from another in certain terms, conditions, or parameters.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d23cf08190925510344fa36f57 |
completed | April 19, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:49 a.m.