Triple
T15638634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pharmacy Council of Pakistan |
E376008
|
entity |
| Predicate | professionRegulated |
P9508
|
FINISHED |
| Object | pharmacists |
—
|
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: pharmacists | Statement: [Pharmacy Council of Pakistan, professionRegulated, pharmacists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionRegulated Context triple: [Pharmacy Council of Pakistan, professionRegulated, pharmacists]
-
A.
hasRegulatedProfession
Indicates that an entity practices or is associated with a profession that is formally regulated by laws, standards, or licensing authorities.
-
B.
regulatesProfession
chosen
Indicates that one entity has authority to control, oversee, or set rules governing the practice of a particular profession by another entity.
-
C.
professionalBody
Indicates that an entity is a formal organization that represents, regulates, or supports members of a particular profession.
-
D.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
E.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eba51f08190ac5d9de7fc89405a |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.