Triple
T35329458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HIA Desgenettes |
E1020277
|
entity |
| Predicate | hasPharmacyService |
P87983
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [HIA Desgenettes, hasPharmacyService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPharmacyService Context triple: [HIA Desgenettes, hasPharmacyService, yes]
-
A.
hasPharmacies
Indicates that one entity possesses, operates, or is associated with one or more pharmacies.
-
B.
hasPharmacyDepartment
chosen
Indicates that an entity includes or is associated with a dedicated pharmacy department or unit.
-
C.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
D.
hasDrug
Indicates that an entity possesses, is treated with, or is associated with a particular drug.
-
E.
hasServiceCenter
Indicates that an entity maintains or is associated with a service center that provides support, repair, or maintenance services.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:03 p.m.