Triple
T14117552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Soopers |
E339810
|
entity |
| Predicate | hasPharmacy |
P107963
|
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: [King Soopers, hasPharmacy, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPharmacy Context triple: [King Soopers, hasPharmacy, true]
-
A.
hasPharmacies
chosen
Indicates that one entity possesses, operates, or is associated with one or more pharmacies.
-
B.
hasPharmacyDepartment
Indicates that an entity includes or is associated with a dedicated pharmacy department or unit.
-
C.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
D.
hasConvenienceStore
Indicates that one entity possesses, contains, or is associated with a convenience store.
-
E.
hasPharmacySchool
Indicates that an institution or entity includes, operates, or is affiliated with a school or program dedicated to the study and training of pharmacy.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de609322ac8190bb389ca250882af5 |
completed | April 14, 2026, 3:43 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.