Triple
T37783230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loopy Landscapes |
E941883
|
entity |
| Predicate | numberOfScenariosAdded |
—
|
GENERATED |
| Object | over 30 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfScenariosAdded Context triple: [Loopy Landscapes, numberOfScenariosAdded, over 30]
-
A.
numberOfScenes
Indicates the total count of distinct scenes associated with or contained within an entity.
-
B.
plannedNumberOfTests
Indicates the total count of tests that are intended or scheduled to be conducted for a given context or period.
-
C.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
-
D.
numberOfConfigurations
Indicates the total count of distinct configurations associated with or applicable to a given entity or situation.
-
E.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
- F. None of above. chosen
Provenance (1 batch)
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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
Created at: May 3, 2026, 4:19 p.m.