Triple
T17521255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MuJoCo environments |
E426682
|
entity |
| Predicate | typicalRewardStructure |
P117907
|
FINISHED |
| Object | dense reward |
—
|
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: dense reward | Statement: [MuJoCo environments, typicalRewardStructure, dense reward]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRewardStructure Context triple: [MuJoCo environments, typicalRewardStructure, dense reward]
-
A.
describesReward
Indicates that one entity provides an explanation or specification of the reward associated with another entity or action.
-
B.
rewardProfile
chosen
Indicates the pattern or structure of rewards an entity receives or is expected to receive, such as how, when, and under what conditions rewards are allocated.
-
C.
benefitStructure
Indicates a relationship where one entity defines, organizes, or governs the benefits (such as advantages, compensations, or perks) provided to or associated with another entity.
-
D.
rewardModel
Indicates a relationship where one entity serves as a model or framework for assigning rewards or evaluating outcomes for another entity or process.
-
E.
typicalAwardAmount
Indicates the usual or most common amount of an award given in this relationship.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d2f79881909556894728e255ab |
completed | April 19, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.