Triple
T32304684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treuhandanstalt |
E825330
|
entity |
| Predicate | numberOfEmployeesAffected |
—
|
GENERATED |
| Object | millions |
—
|
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: numberOfEmployeesAffected Context triple: [Treuhandanstalt, numberOfEmployeesAffected, millions]
-
A.
estimatedAffectedPeople
chosen
Indicates the estimated number of people expected to be impacted by a particular event, condition, or action.
-
B.
affectedPeople
Indicates the people who are impacted or influenced by a particular event, action, or condition.
-
C.
numberOfWorkersFired
Indicates the quantity of workers who were dismissed or terminated from their jobs.
-
D.
standAffected
Indicates that an entity is in a state or position of being impacted or influenced by another entity or event.
-
E.
numberOfEmployeesDate
Indicates the specific date on which the recorded number of employees for an entity is valid or measured.
- F. None of above.
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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 12:45 a.m.