Triple
T7338062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diehard |
E169179
|
entity |
| Predicate | hasDiscreteTimeSteps |
P75141
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Diehard, hasDiscreteTimeSteps, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiscreteTimeSteps Context triple: [Diehard, hasDiscreteTimeSteps, true]
-
A.
timeContinuousOrDiscrete
Indicates whether the time dimension in a given context is modeled as a continuous flow or as discrete, separate time points.
-
B.
timeDiscretization
chosen
Indicates how a continuous or overall time period is divided into discrete intervals or steps for representation or processing.
-
C.
timeDiscretizationFormula
Indicates a relationship where a specific mathematical formula is used to convert or approximate continuous time into discrete time steps for analysis or computation.
-
D.
hasTimeDimension
Indicates that something possesses or is associated with a temporal aspect, such as duration, point in time, or time-based variation.
-
E.
hasTimeDepth
Indicates that something possesses or spans a measurable extent of time, such as duration, historical depth, or temporal layering.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.