Triple
T32510573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Target pharmacy and clinic businesses |
E830918
|
entity |
| Predicate | numberOfClinicsAtAcquisition |
—
|
GENERATED |
| Object | 80 |
—
|
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: numberOfClinicsAtAcquisition Context triple: [Target pharmacy and clinic businesses, numberOfClinicsAtAcquisition, 80]
-
A.
hasNumberOfClinics
chosen
Indicates the quantity of clinics associated with or belonging to a given entity.
-
B.
numberOfHospitals
Indicates the total count of hospitals associated with a given entity or within a specified context.
-
C.
numberOfDrillingCenters
Indicates the quantity of drilling centers associated with or involved in a given entity or context.
-
D.
hasNumberOfAgencies
Indicates the quantity of agencies associated with or linked to a given entity.
-
E.
numberOfStores
Indicates the total count of stores associated with a given entity or context.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
Created at: May 1, 2026, 1 a.m.