Triple
T35335332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lévy processes |
E1020434
|
entity |
| Predicate | timeParameter |
P82883
|
FINISHED |
| Object | continuous time |
—
|
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: continuous time | Statement: [Lévy processes, timeParameter, continuous time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeParameter Context triple: [Lévy processes, timeParameter, continuous time]
-
A.
timingParameter
chosen
Indicates a relationship where one entity specifies or controls a temporal setting, constraint, or configuration parameter that determines the timing behavior of another entity or process.
-
B.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
C.
timeProperty
Indicates that one entity specifies, constrains, or characterizes a temporal aspect or timing-related attribute of another entity.
-
D.
timeType
Indicates the specific temporal category or classification associated with a time-related entity or value (e.g., duration, point in time, interval, or recurrence type).
-
E.
timePeriodFormulated
Indicates the time period during which something (such as a concept, theory, or plan) was formulated or developed.
- 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_69f76debb4e08190be52d89b8af2392d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: May 3, 2026, 4:03 p.m.