Triple
T17521281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MuJoCo environments |
E426682
|
entity |
| Predicate | timeStep |
P75141
|
FINISHED |
| Object | fixed simulation timestep |
—
|
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: fixed simulation timestep | Statement: [MuJoCo environments, timeStep, fixed simulation timestep]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeStep Context triple: [MuJoCo environments, timeStep, fixed simulation timestep]
-
A.
timeSteppingDirection
Indicates the direction in which time progresses or is advanced within a process, simulation, or sequence of steps.
-
B.
timeDiscretization
chosen
Indicates how a continuous or overall time period is divided into discrete intervals or steps for representation or processing.
-
C.
timeOfIntegration
Indicates the specific point or period in time when one entity is incorporated, combined, or merged into another system, process, or structure.
-
D.
timeSampling
Indicates that one entity specifies how or at what intervals another entity is sampled or measured over time.
-
E.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
- 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.